Econstudentlog

A few diabetes papers of interest

i. Real-World Costs of Continuous Insulin Pump Therapy and Multiple Daily Injections for Type 1 Diabetes: A Population-Based and Propensity-Matched Cohort From the Swedish National Diabetes Register.

“Continuous subcutaneous insulin infusion, or insulin pump, therapy for individuals with type 1 diabetes has increased gradually since the 1980s. Yet, a Cochrane review concluded in 2010 that although some evidence indicates that insulin pumps improve glycemic control compared with standard multiple daily injection (MDI) therapy, insufficient evidence exists regarding mortality, morbidity, and costs (1). A systematic review of cost-effectiveness studies summarized comparisons of insulin pump and MDI therapy using model analyses to describe the expected impact on long-term costs, development of complications, and quality of life (2). Five of the studies reported long-term discounted incremental costs of insulin pumps of $20,000–$40,000, whereas two studies reported lower and one higher additional costs for insulin pump therapy. However, real-world data on health care and societal costs of insulin pump therapy compared with MDI therapy are scarce. […] Data from the Swedish National Diabetes Register (NDR) have shown a lower incidence of some cardiovascular events and all-cause mortality for individuals with type 1 diabetes on insulin pump therapy in 2005–2012 (5). Registration of insulin pump therapy started in 2002 in the NDR, and use of pump therapy among individuals with type 1 diabetes increased from 10% in 2002 to 22% in 2015 (6). A relevant research question from a health care planning perspective is whether real-world data match earlier model-based predictions for differences in resource use and costs. We investigated from a societal perspective costs of continuous insulin pump and MDI therapy in clinical practice for individuals with type 1 diabetes using the NDR and a 9-year observational panel from national health and socioeconomic data registers.”

“The final analysis set included data in 2005–2013 for 14,238 individuals with type 1 diabetes, of whom 4,991 had insulin pump therapy (598 individuals switched to pump therapy in 2005 or later after original inclusion as control subjects with MDI). We had 73,920 person-years of observation with a mean follow-up of 5 years per subject. […] The distribution of annual costs was left-skewed with a tail of observations with high costs, although the most person-years incurred costs corresponding to typical insulin therapy and up to two regular follow-up appointments […] The difference in the annual total cost between the therapy groups was $3,923 (95% CI $3,703–$4,143). […] The difference in annual medication costs, including disposables, was $3,600, indicating that they contributed significantly to overall annual cost differences. Pump users had more outpatient appointments (3.8 vs. 3.5 per year; P < 0.001) and were less likely to have person-years without use of outpatient or inpatient care (9% vs. 12% of person-years). Even with a median duration of diabetes of 21 years at baseline, the mean cost per patient-year of cardiovascular comorbidities and diabetic complications was low because of the overall low rates of events. […] Total annual costs increased with age for both insulin therapies, and pump therapy was associated with higher costs across age-groups. However, the cost increments for insulin pump therapy decreased with age (differences ranging from 56% for those 18–27 years of age to 44% for those ≥48 years [reference: MDI 18–27 years]). Total costs were higher for women but decreased with years of education and disposable income. […] The level of HbA1c at baseline affected the differences in average annual cost between study groups: the smallest difference ($2,300) was observed for individuals with HbA1c ≥8.6% (≥70 mmol/mol) and the greatest difference for individuals with HbA1c 6.5–8.5% (48–69 mmol/mol) at baseline [pump $12,824 vs. MDI $8,083; P < 0.001, US].”

“The study cohort was young (mean baseline age 34 years) with relatively few diabetic complications in both study groups. For instance, 1.5% of person-years had a cardiovascular event, and 5% had at least one health care contact with a cardiovascular diagnosis.

Observational studies provide a better indication of what is achieved in daily medical practice than randomized controlled studies (12). The strength of this observational study is the size and completeness of the study population, with virtually all adults with type 1 diabetes in Sweden included, longitudinal national register data, and a matching technique that accounts for time-variant variables, including diabetes duration, diabetes-related conditions and comorbidities, and demographic and socioeconomic factors. With the use of time-varying propensity scores, we allowed selected MDI control subjects to switch to pump therapy rather than to condition their eligibility or noneligibility on a future therapeutic change. The plentiful data allowed us to match two control subjects to each pump user to account for the variance in cost variables and enabled extensive subgroup and sensitivity analyses.”

“We observed only a few deaths (n = 353 [2.5% main analysis sample], no difference pump vs. MDI [OR 0.98 (95% CI 0.79–1.23)]) and similar rates of cardiovascular disease for pump and MDI in this study, except for borderline significantly fewer events with angina in the pump group. A heterogeneous distribution of events was found across nontreatment characteristics: ∼70% of all cardiovascular events occurred among individuals 48 years of age or older, and >90% of the events occurred among individuals with diabetes duration ≥20 years at baseline.

A lack of comparable calculations of total costs of diabetes treatment has been published to date, but cost-effectiveness studies of pump and MDI therapy have predicted long-term costs for the two treatment methods. Roze et al. (2) performed a meta-review of model-based studies that compared pump therapy and MDI, concluding that pump therapy can be cost effective. Published models have identified change in HbA1c and reduction in number of hypoglycemic events as important drivers of costs. A Swedish health technology assessment review in 2013 did not find evidence for differences in severe hypoglycemia between pump therapy and MDI but identified indications of lower HbA1c (13). […] Subgroup analyses by age indicated that the value of improved prevention may take time to manifest. Approximately one-quarter of additional annual costs for individuals with type 1 diabetes age ≥48 years (∼25% of the cohort) could be prevented with insulin pump therapy.

Whether insulin pump therapy is cost efficient ultimately depends on therapeutic effects beyond resource use and costs as well as on how much the payer is prepared to invest in additional quality-adjusted life-years (QALYs). If the payer’s cost-effectiveness threshold is $50,000 per QALY gained, treatment needs to provide an average annual additional 0.1 QALY or, on the basis of the subgroup analyses, gains in the range of 0.06–0.12 QALY. Similarly, with a threshold of $100,000, the required gain in annual QALYs would have to be between 0.03 and 0.06. The average cost difference between insulin therapies in this study and a 20-year time horizon roughly correspond to a discounted (3%) lifetime cost difference of $62,000. The corresponding cost for a 40-year time horizon is $95,000. Previous model-based cost-effectiveness analyses have reported expected discounted QALY gains for a lifetime in the range of 0.46–1.06 QALYs, whereas the estimates of the increase in discounted lifetime costs varied (2).”

ii. Cumulative Risk of End-Stage Renal Disease Among Patients With Type 2 Diabetes: A Nationwide Inception Cohort Study.

“One of the most devastating complications of diabetes is chronic kidney disease. Relative to the general population, persons with diabetes have a 5- to 13-fold risk of end-stage renal disease (ESRD) (46). ESRD extensively increases risk of death among patients with diabetes (79), and diabetes is the most common cause of ESRD in most industrialized countries (10); a study of 18 European countries showed that type 2 diabetes was the most frequent renal disease leading to initiation of renal replacement therapy (11).

Most earlier studies of the incidence of ESRD in diabetes have used prevalence cohorts, which means that patients have not been followed since their diabetes diagnosis. Patients with all types of diabetes typically have been included, and the incidence rate of ESRD has been 1–9 per 1,000 patient-years (4,1214), with larger estimates among African Americans and those with a longer duration of diabetes. Notably, a prevalence cohort study from Italy including only patients with type 2 diabetes showed that only 10 of 1,408 patients developed ESRD over a 10-year follow-up (15). To our knowledge, only two inception cohort studies have addressed the incidence of ESRD. The UK Prospective Diabetes Study followed 5,097 patients with newly diagnosed type 2 diabetes, only 14 of whom required renal replacement therapy during the median follow-up of 10.4 years (16). However, the cumulative risk was not computed, and any subgroup analyses would not have been possible because of the small number of patients who developed ESRD. A population-based study from Saskatchewan, Canada, included 90,429 incident cases of diabetes among the adult study population, and the results showed an almost threefold risk of ESRD among indigenous patients (17). Among nonindigenous patients, the cumulative incidence of ESRD was ∼1–2% at 20 years since the diabetes diagnosis.

We and others have estimated the cumulative risk of ESRD in inception cohorts of patients with type 1 diabetes (1821). Although type 2 diabetes is a major cause of ESRD, cumulative risk of ESRD after type 2 diabetes has been diagnosed is not well known. Here, we present the cumulative risk of ESRD during a 24-year follow-up of a nationwide population-based cohort of 421,429 patients newly diagnosed with type 2 diabetes in 1990–2011.”

“Of 421,429 patients diagnosed with type 2 diabetes in 1990–2011, 1,516 developed ESRD and 150,524 died before the end of 2013. The total number of patient-years of type 2 diabetes was 3,458,797 […]. The median follow-up was 6.82 years. A sex difference was found for age distribution: 70% of women and 55% of men were 60 years or older when type 2 diabetes was diagnosed. […] The cumulative risk of ESRD was 0.29% at 10 years and 0.74% at 20 years since the diagnosis of type 2 diabetes. […] Men had a 93% higher risk of ESRD than women. […] this male predominance is a common finding for all causes of ESRD (10). […] As an alternative analysis, the incidence rate of ESRD was calculated among all prevalent cases of type 2 diabetes in the time periods 1990–1999 and 2000–2011, thus including patients who were diagnosed with type 2 diabetes before 1990 but who contributed patient-years in 1990–2013 […]. During a total of 4,345,251 patient-years, 2,127 patients developed ESRD, resulting in an incidence rate of 0.49 per 1,000 patient-years (95% CI 0.47–0.51). The incidence rate was higher among men (0.66 [95% CI 0.63–0.70]) than among women (0.33 [95% CI 0.31–0.35]) and in 2000–2013 (0.53 [95% CI 0.51–0.56]) than in 1990–1999 (0.37 [95% CI 0.34–0.41]). The incidence rate of ESRD had increased most among men older than 70 years. For both men and women, the incidence rate of ESRD peaked among those aged 60–79 years.”

“Among patients diagnosed with type 2 diabetes between 1990 and 2011, the cumulative risk of death was 34% at 10 years and 64% at 20 years since the diagnosis of diabetes. […] Patients aged 70–79 years when diabetes was diagnosed had an eightfold risk of death during the follow-up compared with those aged 40–49 years. When calculating HR for death, occurrence of ESRD was included in the multivariable model as a time-dependent variable […], and ESRD increased the risk of death 4.2-fold during follow-up. […] In the interaction analysis, sex modified the effects of age and ESRD on HR for death. Among men, ESRD increased risk of death 3.8-fold and among women, 5.6-fold. Age (70–79 vs. 40–49 years) showed an HR for death of 7.4 among men and 9.8 among women. Also, a statistically significant interaction occurred between age and ESRD during follow-up, showing a weaker association between ESRD and risk of death among those aged 70 years or older (HR 3) than among those younger than 60 years (HR 5).”

“Our study shows that risk of ESRD is small among people with type 2 diabetes. This may seem unexpected, because a substantial proportion of patients are entering early stages of chronic kidney disease, with 25% of patients having microalbuminuria and 5% having macroalbuminuria 10 years after their diabetes diagnosis (16). These early stages of kidney disease are associated with increased premature mortality; this contributes to the fact that relatively few patients develop ESRD, as death is a common competing risk event. However, diabetes is the most common cause of ESRD in most industrialized countries, and because of a high and increasing prevalence of diabetes among the general population, a considerable absolute number of patients with type 2 diabetes need dialysis therapy (10,11). Our findings are important for clinicians who inform patients with type 2 diabetes about the associated risks and complications. […] Notably, people diagnosed with type 2 diabetes at an older age have a lower risk of ESRD and a higher risk of death than those diagnosed at a younger age. The cumulative risk of ESRD and death has decreased since the early 1990s among people with type 2 diabetes.”

iii. Impact of Age of Onset, Puberty, and Glycemic Control Followed From Diagnosis on Incidence of Retinopathy in Type 1 Diabetes: The VISS Study.

“In a population-based observational study, HbA1c for 451 patients diagnosed with diabetes before 35 years of age during 1983–1987 in southeast Sweden was followed for up to 18–24 years from diagnosis. Long-term mean weighted HbA1c (wHbA1c) was calculated. Retinopathy was evaluated by fundus photography and analyzed in relation to wHbA1c levels.”

RESULTS Lower wHbA1c, diabetes onset ≤5 years of age, and diabetes onset before puberty, but not sex, were associated with longer time to appearance of simplex retinopathy. Proliferative retinopathy was associated only with wHbA1c. The time to first appearance of any retinopathy decreased with increasing wHbA1c. Lower wHbA1c after ≤5 years’ diabetes duration was associated with later onset of simplex retinopathy but not proliferative retinopathy. With time, most patients developed simplex retinopathy, except for those of the category wHbA1c ≤50 mmol/mol (6.7%), for which 20 of 36 patients were without any retinopathy at the end of the follow-up in contrast to none of 49 with wHbA1c >80 mmol/mol (9.5%). […] At the end of the follow-up only 54 patients (12.5%) had no signs of retinopathy and 145 (33.6%) had slight simplex, 175 (40.5%) moderate simplex, and 57 (13.2%) proliferative retinopathy.”

CONCLUSIONS Onset at ≤5 years of age and lower wHbA1c the first 5 years after diagnosis are associated with longer duration before development of simplex retinopathy. There is a strong positive association between long-term mean HbA1c measured from diagnosis and up to 20 years and appearance of both simplex and proliferative retinopathy.”

“Complete avoidance of retinopathy in patients with type 1 diabetes evidently requires a very tight glycemic control, which is very difficult to achieve with the treatment tools available today and is also dangerous because of the risk of severe hypoglycemia (27). […] In clinical practice, it is of great importance to find the balance between the risk of potentially dangerous hypoglycemic events and quality of life and the risk of severe microvascular complications to be able to recommend an evidence-based optimal level of HbA1c both in the short-term and in the long-term. The observation that wHbA1c before and during puberty did not influence the prevalence of proliferative retinopathy at 20 years’ diabetes duration is of clinical importance in the setting of targets for glycemic control in young children for whom severe hypoglycemia might be especially dangerous.

Simplex retinopathy is not sight threatening, even if advanced simplex retinopathy is a risk factor for proliferative retinopathy (13). However, simplex retinopathy may regress, and in our study simplex retinopathy regressed in a group of patients with mean wHbA1c 7.0% (SD 0.7%) (53 [8] mmol/mol). Proliferative retinopathy is clinically more relevant and should be avoided. We previously showed that the threshold for proliferative retinopathy is higher than for simplex retinopathy (28). Proliferative retinopathy did not occur in this material in patients with wHbA1c <7.6% (60 mmol/mol), which indicates what should be an important goal for glycemic control. This is in close agreement with the position statement for type 1 diabetes in children and adolescents recently issued by the American Diabetes Association recommending an HbA1c target of <7.5% (58 mmol/mol) (31).

In summary, after 20 years of diabetes duration, there is a strong positive association between long-term mean wHbA1c followed from diagnosis and appearance of both simplex and proliferative retinopathy. Diabetes onset at <5 years of age and lower wHbA1c the first 5 years after diagnosis are associated with longer duration before development of simplex retinopathy but not proliferative retinopathy. Proliferative retinopathy does not appear in patients with wHbA1c <7.6% (60 mmol/mol).”

iv. Association of Diabetes and Glycated Hemoglobin With the Risk of Intracerebral Hemorrhage: A Population-Based Cohort Study.

“Spontaneous intracerebral hemorrhage (ICH) is a devastating condition accounting for 10–15% of all stroke cases. It is associated with a dismal prognosis, as only 38% of affected patients survive the first year (1).

Type 2 diabetes affects more than 415 million adults worldwide and is a well-known contributor to cardiovascular morbidity, cognitive decline, and all-cause mortality (2). Although diabetes is an independent risk factor for ischemic stroke (3), as yet there is no conclusive evidence for the association between diabetes and ICH, as previous studies showed conflicting results (48). […] We sought to determine 1) the association of diabetes and ICH and 2) the relationship between HbA1c levels and ICH in a large nationwide population-based cohort. […] We sought to determine 1) the association of diabetes and ICH and 2) the relationship between HbA1c levels and ICH in a large nationwide population-based cohort.”

Do keep in mind in the following that although the link between hemorrhagic stroke and diabetes is somewhat unclear (…for example: “in the Copenhagen Stroke Registry, hemorrhagic stroke was even six times less frequent in diabetic patients than in non-diabetic subjects (102). […] However, in another prospective population-based study DM was associated with an increased risk of primary intracerebral hemorrhage (103).”), the link between ischemic stroke and diabetes is strong and well-established – see the link for more details.

“This study is based on data from the computerized database of Clalit Health Services (CHS), which provides inclusive health care for more than half of the Israeli population. […] 313,130 patients had a preexisting diagnosis of diabetes and 1,167,585 individuals were without diabetes. Patients with diabetes had to have at least one test result for HbA1c in the 2 years before cohort entry (n = 297,486). Cohort participants (n = 1,465,071) were followed-up until reaching the study outcome (ICH), death, loss to follow-up, or end of follow-up at 31 December 2017 — whichever came first. […] The outcome of interest was ICH, defined as primary discharge diagnosis with ICH (ICD-9 code 431). […] Overall 4,170 patients had incident ICH during a mean (SD) follow-up of 7.3 (1.8) years and 10,730,915 person-years, reflecting an ICH crude incidence rate of 38.8 per 100,000 person-years. […] The strongest risk factors for ICH were prior ICH, prior stroke/transient ischemic attack (TIA), use of anticoagulation, hypertension, alcohol abuse, male sex, Arab ethnicity, chronic liver disease, and older age.”

“Because of the large number of potential confounders, we performed adjustment for a disease risk score (DRS), a summary measure of disease probability. The DRS was estimated using a Cox proportional hazards regression model for ICH outcome that included most clinically relevant ICH risk factors and other clinical covariates likely to be correlated with ICH […]. In comparison with conventional multivariate analyses, adjustment for the single variable DRS increases the efficiency of the analyses (16,17). It has been shown than the DRS and propensity score methods had comparable performance and that DRS has an advantage when multiple comparison groups are studied (16,17). […] The crude incidence rate of ICH was 78.9 per 100,000 person-years among patients with diabetes and 29.4 per 100,000 person-years among patients without diabetes (crude HR 2.69 [95% CI 2.53–2.87]) (Table 2). Diabetes remained significantly associated with ICH after adjustment for DRS (1.36 [1.27–1.45]). […] The results were unchanged after exclusion of new cases of diabetes and after censoring at the time of new diabetes diagnosis occurring during follow-up: DRS-adjusted HR 1.37 (95% CI 1.28–1.46) and 1.38 (1.29–1.47), respectively. […] The risk of ICH was directly associated with diabetes duration. Compared with the group without diabetes, the DRS-adjusted HR was 1.23 (95% CI 1.12–1.35) and 1.44 (1.34–1.56) for diabetes duration ≤5 years and >5 years, respectively. The corresponding HRs with adjustment for propensity score were 1.27 (1.15–1.41) and 1.65 (1.50–1.80), respectively […] HbA1c was significantly associated with ICH among patients with diabetes: adjusted HR 1.14 (95% CI 1.10–1.17) for each 1% increase in HbA1c […] HbA1c appears to have a nonlinear J-shaped relationship with ICH (Pnonlinearity = 0.0186), with the lowest risk observed at HbA1c of 6.5% (48 mmol/mol). […] The risk of ICH among patients with HbA1c of 6.5–6.7% (48–50 mmol/mol) was comparable with the risk in patients without diabetes, suggesting that albeit having diabetes, patients with good, but not extreme, diabetes control do not appear to have excess risk of ICH compared with patients without diabetes.”

“To date, the exact mechanisms underlying the association between diabetes, HbA1c, and ICH remain unknown. […] In summary, our study suggests that diabetes is associated with increased risk of ICH that is directly associated with diabetes duration. ICH and HbA1c appear to have a J-shaped relationship, suggesting that both poor control as well as extreme intensive diabetes control might be associated with increased risk.”

v. Nonproteinuric Versus Proteinuric Phenotypes in Diabetic Kidney Disease: A Propensity Score–Matched Analysis of a Nationwide, Biopsy-Based Cohort Study.

“Mainly based on the analysis of the data from patients with type 1 diabetes, in the clinical course of diabetic kidney disease it has long been considered that an increase of albuminuria, from normoalbuminuria (urine albumin-to-creatinine ratio ratio [UACR] <30 mg/g) to microalbuminuria (UACR 30–299 mg/g) to macroalbuminuria (UACR ≥300 mg/g), precedes the progression of renal decline (defined as estimated glomerular filtration rate [eGFR] <60 mL/min/1.73 m2) (13). Morphological changes known as nodular glomerular sclerosis (Kimmelstiel-Wilson nodule) have also been observed in patients with diabetes and loss of renal function (4,5). Therefore, patients with diabetes and reduced renal function are deemed to have overt proteinuria with nodular glomerular sclerosis. Recently, however, cumulative evidence from several cross-sectional studies revealed that a proportion of patients with type 2 diabetes develop progression of renal decline without proteinuria (macroalbuminuria) or even without microalbuminuria, suggesting the existence of a nonproteinuric phenotype of diabetic kidney disease defined as eGFR <60 mL/min/1.73 m2 and UACR <300 mg/g (611). Despite increasing attention, few clinical trials and longitudinal studies in type 2 diabetes include individuals without proteinuria or individuals with biopsy-proven diabetic kidney disease, and therefore their clinicopathological characteristics, renal prognosis, and all-cause mortality are very limited.

Similar to the U.S. and most countries in Europe, Japan has been suffering from the expanding trend in the continued increase of the prevalence of diabetic kidney disease that leads to end-stage renal disease (ESRD) and high mortality (1215). Commissioned by the Ministry of Health, Labour and Welfare and the Japan Agency for Medical Research and Development with a goal of better understanding and halting the pandemic of diabetic kidney disease, we established a nationwide biopsy-based cohort of diabetic kidney disease with followed-up data, including ESRD and death ascertainment. Using this nationwide cohort and propensity score–matching methods, we aimed to investigate clinicopathological characteristics, renal prognosis, and mortality in patients with the nonproteinuric phenotype of diabetic kidney disease compared with patients with the classical proteinuric phenotype of diabetic kidney disease.”

“This is a retrospective study of patients who underwent clinical renal biopsy performed from 1 January 1985 to 31 December 2016 and had a pathological diagnosis of diabetic kidney disease at [one of] 18 hospitals in Japan […] 895 patients underwent clinical renal biopsy and had a pathological diagnosis of diabetic kidney disease in our cohort […]. We identified 526 who had an eGFR <60 mL/min/1.73 m2 at the time of biopsy. Among them, 88 had nonproteinuric diabetic kidney disease (UACR <300 mg/g), and 438 had proteinuric diabetic kidney disease (UACR ≥300 mg/g) at baseline. After propensity score matching, the nonproteinuric diabetic kidney disease group comprised 82 patients and the proteinuric diabetic kidney disease group comprised 164 patients […] In propensity score–matched cohorts, the blood pressure in patients with nonproteinuric diabetic kidney disease was better controlled compared with patients with proteinuric diabetic kidney disease, although patients with nonproteinuric diabetic kidney disease were less prescribed RAAS blockade. Patients with nonproteinuric diabetic kidney disease had lower total cholesterol levels and higher hemoglobin levels. For pathological characteristics, there was a difference in classification assignment for diabetic kidney disease between the nonproteinuric diabetic kidney disease group and proteinuric diabetic kidney disease group. […] Compared with the proteinuric diabetic kidney disease group, the nonproteinuric diabetic kidney disease group had less severe interstitial and vascular lesions. […] In a multivariable logistic regression model, older age, lower systolic blood pressure, higher hemoglobin level, and higher HbA1c were significantly associated with a higher odds of nonproteinuric diabetic kidney disease.”

“After a median follow-up of 1.8 years (IQR 0.9–3.7) from the date of renal biopsy, 297 (56%) of the 526 patients had renal events. The 5-year CKD progression-free survival was 33.2% (95% CI 28.4–38.2%) for all patients, 86.9% (95% CI 73.1–93.9%) for the nonproteinuric diabetic kidney disease group, and 24.5% (95% CI 19.8–29.5%) for the proteinuric diabetic kidney disease group (log-rank test P < 0.001) […]. The same trend was seen in the propensity score–matched cohort: After a median follow-up of 1.9 years (IQR 0.9–5.0) from the date of renal biopsy, 124 (50%) of the 246 matched patients had renal events. The 5-year CKD progression-free survival was 46.4% (95% CI 38.7–53.6%) for all patients, 86.6% (95% CI 72.5–93.8%) for the nonproteinuric diabetic kidney disease group, and 30.3% (95% CI 22.4–38.6%) for the proteinuric diabetic kidney disease group (log-rank test P < 0.001) […]. Similarly, for the secondary outcome (all-cause mortality), after a median follow-up of 2.7 years (IQR 1.1–5.7) from the date of renal biopsy, 55 (10%) of the 526 patients had death events. The 5-year death-free survival was 89.7% (95% CI 85.6–92.7%) for all patients, 98.4% (95% CI 89.1–99.8%) for the nonproteinuric diabetic kidney disease group, and 87.5% (95% CI 82.5–91.2%) for the proteinuric diabetic kidney disease group (log-rank test P < 0.001) […]. The same trend was seen in the propensity matched cohort: After a median follow-up of 3.1 years (IQR 1.3–7.0) from the date of renal biopsy, 35 (14%) of the 246 matched patients had death events. The 5-year death-free survival was 88.2% (95% CI 82.0–92.3%) for all patients, 98.3% (95% CI 88.7–99.8%) for the nonproteinuric diabetic kidney disease group, and 82.6% (95% CI 73.6–88.8%) for the proteinuric diabetic kidney disease group (log-rank test P = 0.005) […] The overall CKD progression incidence was significantly lower in the nonproteinuric diabetic kidney disease group (30 [95% CI 18–50] per 1,000 person-years) than in the proteinuric diabetic kidney disease group (231 [95% CI 191–278] per 1,000 person-years; crude HR 0.15 [95% CI 0.08–0.26]). After adjustment for age, sex, known duration of diabetes, and baseline eGFR, the risk of CKD progression remained lower in the nonproteinuric diabetic kidney disease cohort than in the proteinuric diabetic kidney disease cohort (adjusted HR 0.13 [95% CI 0.08–0.24]). The risk of CKD progression was consistently lower in the nonproteinuric diabetic kidney disease group than in the proteinuric diabetic kidney disease group when stratified by potential confounders such as age, sex, obesity, retinopathy, smoking status, use of RAAS blockade, hypertension, dyslipidemia, poor glycemic control, lower eGFR, and pathological findings.”

“In conclusion, in propensity score–matched cohorts of biopsy-proven nonproteinuric diabetic kidney disease and proteinuric diabetic kidney disease, patients with nonproteinuric diabetic kidney disease had lower blood pressure with less frequent typical pathological lesions and were at lower risk of CKD progression and all-cause mortality. Further studies are warranted to confirm these findings in other cohorts.”

vi. Single herbal medicine for diabetic retinopathy (Cochrane).

“Diabetic retinopathy is one of the major causes of blindness and the number of cases has risen in recent years. Herbal medicine has been used to treat diabetes and its complications including diabetic retinopathy for thousands of years around the world. However, common practice is not always evidence‐based. Evidence is needed to help people with diabetic retinopathy or doctors to make judicious judgements about using herbal medicine as treatment.”

“We included 10 studies involving 754 participants, of which nine were conducted in China and one in Poland. In all studies, participants in both groups received conventional treatment for diabetic retinopathy which included maintaining blood glucose and lipids using medicines and keeping a stable diabetic diet. In three studies, the comparator group also received an additional potentially active comparator in the form of a vasoprotective drug. The single herbs or extracts included Ruscus extract tablet, Sanqi Tongshu capsule, tetramethylpyrazine injection, Xueshuantong injection, Puerarin injection and Xuesaitong injection. The Sanqi Tongshu capsule, Xueshuantong injection and Xuesaitong injection were all made from the extract of Radix Notoginseng (San qi) and the main ingredient was sanchinoside. The risk of bias was high in all included studies mainly due to lack of masking (blinding). None of the studies reported the primary outcome of this review, progression of retinopathy.

Combined analysis of herbal interventions suggested that people who took these herbs in combination with conventional treatment may have been more likely to gain 2 or more lines of visual acuity compared to people who did not take these herbs when compared to conventional intervention alone at the end of treatment (RR 1.26, 95% CI 1.08 to 1.48; 5 trials, 541 participants; low‐certainty evidence). Subgroup analyses based on the different single herbs found no evidence for different effects of different herbs, but the power of this analysis was low. […]

Authors’ conclusions

No conclusions could be drawn about the effect of any single herb or herbal extract on diabetic retinopathy from the current available evidence. It was difficult to exclude the placebo effect as a possible explanation for observed differences due to the lack of placebo control in the included studies. Further adequately designed trials are needed to establish the evidence.”

 

September 25, 2019 Posted by | Diabetes, Epidemiology, Health Economics, Medicine, Nephrology, Ophthalmology, Studies | Leave a comment

A few diabetes papers of interest

i. Identical and Nonidentical Twins: Risk and Factors Involved in Development of Islet Autoimmunity and Type 1 Diabetes.

Some observations from the paper:

“Type 1 diabetes is preceded by the presence of preclinical, persistent islet autoantibodies (1). Autoantibodies against insulin (IAA) (2), GAD (GADA), insulinoma-associated antigen 2 (IA-2A) (3), and/or zinc transporter 8 (ZnT8A) (4) are typically present prior to development of symptomatic hyperglycemia and progression to clinical disease. These autoantibodies may develop many years before onset of type 1 diabetes, and increasing autoantibody number and titers have been associated with increased risk of progression to disease (57).

Identical twins have an increased risk of progression of islet autoimmunity and type 1 diabetes after one twin is diagnosed, although reported rates have been highly variable (30–70%) (811). This risk is increased if the proband twin develops diabetes at a young age (12). Concordance rates for type 1 diabetes in monozygotic twins with long-term follow-up is >50% (13). Risk for development of islet autoimmunity and type 1 diabetes for nonidentical twins is thought to be similar to non-twin siblings (risk of 6–10% for diabetes) (14). Full siblings who inherit both high-risk HLA (HLA DQA1*05:01 DR3/4*0302) haplotypes identical to their proband sibling with type 1 diabetes have a much higher risk for development of diabetes than those who share only one or zero haplotypes (55% vs. 5% by 12 years of age, respectively; P = 0.03) (15). Despite sharing both HLA haplotypes with their proband, siblings without the HLA DQA1*05:01 DR3/4*0302 genotype had only a 25% risk for type 1 diabetes by 12 years of age (15).”

“The TrialNet Pathway to Prevention Study (previously the TrialNet Natural History Study; 16) has been screening relatives of patients with type 1 diabetes since 2004 and follows these subjects with serial autoantibody testing for the development of islet autoantibodies and type 1 diabetes. The study offers longitudinal monitoring for autoantibody-positive subjects through HbA1c testing and oral glucose tolerance tests (OGTTs).”

“The purpose of this study was to evaluate the prevalence of islet autoantibodies and analyze a logistic regression model to test the effects of genetic factors and common twin environment on the presence or absence of islet autoantibodies in identical twins, nonidentical twins, and full siblings screened in the TrialNet Pathway to Prevention Study. In addition, this study analyzed the presence of islet autoantibodies (GADA, IA-2A, and IAA) and risk of type 1 diabetes over time in identical twins, nonidentical twins, and full siblings followed in the TrialNet Pathway to Prevention Study. […] A total of 48,051 sibling subjects were initially screened (288 identical twins, 630 nonidentical twins, and 47,133 full siblings). Of these, 48,026 had an initial screening visit with GADA, IA2A, and IAA results (287 identical twins, 630 nonidentical twins, and 47,109 full siblings). A total of 17,226 participants (157 identical twins, 283 nonidentical twins and 16,786 full siblings) were followed for a median of 2.1 years (25th percentile 1.1 year and 75th percentile 4.0 years), with follow-up defined as at least ≥12 months follow-up after initial screening visit.”

“At the initial screening visit, GADA was present in 20.2% of identical twins (58 out of 287), 5.6% of nonidentical twins (35 out of 630), and 4.7% of full siblings (2,205 out of 47,109) (P < 0.0001). Additionally, IA-2A was present primarily in identical twins (9.4%; 27 out of 287) and less so in nonidentical twins (3.3%; 21 out of 630) and full siblings (2.2%; 1,042 out of 47,109) (P = 0.0001). Nearly 12% of identical twins (34 out of 287) were positive for IAA at initial screen, whereas 4.6% of nonidentical twins (29 out of 630) and 2.5% of full siblings (1,152 out of 47,109) were initially IAA positive (P < 0.0001).”

“At 3 years of follow-up, the risk for development of GADA was 16% for identical twins, 5% for nonidentical twins, and 4% for full siblings (P < 0.0001) (Fig. 1A). The risk for development of IA-2A by 3 years of follow-up was 7% for identical twins, 4% for nonidentical twins, and 2% for full siblings (P = 0.0005) (Fig. 1B). At 3 years of follow-up, the risk of development of IAA was 10% for identical twins, 5% for nonidentical twins, and 4% for full siblings (P = 0.006) […] In initially autoantibody-negative subjects, 1.5% of identical twins, 0% of nonidentical twins, and 0.5% of full siblings progressed to diabetes at 3 years of follow-up (P = 0.18) […] For initially single autoantibody–positive subjects, at 3 years of follow-up, 69% of identical twins, 13% of nonidentical twins, and 12% of full siblings developed type 1 diabetes (P < 0.0001) […] Subjects who were positive for multiple autoantibodies at screening had a higher risk of developing type 1 diabetes at 3 years of follow-up with 69% of identical twins, 72% of nonidentical twins, and 47% of full siblings developing type 1 diabetes (P = 0.079)”

“Because TrialNet is not a birth cohort and the median age at screening visit was 11 years overall, this study would not capture subjects who had initial seroconversion at a young age and then progressed through the intermediate stage of multiple antibody positivity before developing diabetes.”

“This study of >48,000 siblings of patients with type 1 diabetes shows that at initial screening, identical twins were more likely to have at least one positive autoantibody and be positive for GADA, IA-2A, and IAA than either nonidentical twins or full siblings. […] risk for development of type 1 diabetes at 3 years of follow-up was high for both single and multiple autoantibody–positive identical twins (62–69%) and multiple autoantibody–positive nonidentical twins (72%) compared with 47% for initially multiple autoantibody–positive full siblings and 12–13% for initially single autoantibody–positive nonidentical twins and full siblings. To our knowledge, this is the largest prediagnosis study to evaluate the effects of genetic factors and common twin environment on the presence or absence of islet autoantibodies.

In this study, younger age, male sex, and genetic factors were significantly associated with expression of IA-2A, IAA, more than one autoantibody, and more than two autoantibodies, whereas only genetic factors were significant for GADA. An influence of common twin environment (E) was not seen. […] Previous studies have shown that identical twin siblings of patients with type 1 diabetes have a higher concordance rate for development of type 1 diabetes compared with nonidentical twins, although reported rates for identical twins have been highly variable (30–70%) […]. Studies from various countries (Australia, Denmark, Finland, Great Britain, and U.S.) have reported concordance rates for nonidentical twins ∼5–15% […]. Concordance rates have been higher when the proband was diagnosed at a younger age (8), which may explain the variability in these reported rates. In this study, autoantibody-negative nonidentical and identical twins had a low risk of type 1 diabetes by 3 years of follow-up. In contrast, once twins developed autoantibodies, risk for type 1 diabetes was high for multiple autoantibody nonidentical twins and both single and multiple autoantibody identical twins.”

ii. A Type 1 Diabetes Genetic Risk Score Can Identify Patients With GAD65 Autoantibody–Positive Type 2 Diabetes Who Rapidly Progress to Insulin Therapy.

This is another paper in the ‘‘ segment from the February edition of Diabetes Care – multiple other papers on related topics were also included in that edition, so if you’re interested in the genetics of diabetes it may be worth checking out.

Some observations from the paper:

“Type 2 diabetes is a progressive disease due to a gradual reduction in the capacity of the pancreatic islet cells (β-cells) to produce insulin (1). The clinical course of this progression is highly variable, with some patients progressing very rapidly to requiring insulin treatment, whereas others can be successfully treated with lifestyle changes or oral agents for many years (1,2). Being able to identify patients likely to rapidly progress may have clinical utility in prioritization monitoring and treatment escalation and in choice of therapy.

It has previously been shown that many patients with clinical features of type 2 diabetes have positive GAD65 autoantibodies (GADA) and that the presence of this autoantibody is associated with faster progression to insulin (3,4). This is often termed latent autoimmune diabetes in adults (LADA) (5,6). However, the predictive value of GADA testing is limited in a population with clinical type 2 diabetes, with many GADA-positive patients not requiring insulin treatment for many years (4,7). Previous research has suggested that genetic variants in the HLA region associated with type 1 diabetes are associated with more rapid progression to insulin in patients with clinically defined type 2 diabetes and positive GADA (8).

We have recently developed a type 1 diabetes genetic risk score (T1D GRS), which provides an inexpensive ($70 in our local clinical laboratory and <$20 where DNA has been previously extracted), integrated assessment of a person’s genetic susceptibility to type 1 diabetes (9). The score is composed of 30 type 1 diabetes risk variants weighted for effect size and aids discrimination of type 1 diabetes from type 2 diabetes. […] We aimed to determine if the T1D GRS could predict rapid progression to insulin (within 5 years of diagnosis) over and above GADA testing in patients with a clinical diagnosis of type 2 diabetes treated without insulin at diagnosis.”

“We examined the relationship between GADA, T1D GRS, and progression to insulin therapy using survival analysis in 8,608 participants with clinical type 2 diabetes initially treated without insulin therapy. […] In this large study of participants with a clinical diagnosis of type 2 diabetes, we have found that type 1 genetic susceptibility alters the clinical implications of a positive GADA when predicting rapid time to insulin. GADA-positive participants with high T1D GRS were more likely to require insulin within 5 years of diagnosis, with 48% progressing to insulin in this time in contrast to only 18% in participants with low T1D GRS. The T1D GRS was independent of and additive to participant’s age of diagnosis and BMI. However, T1D GRS was not associated with rapid insulin requirement in participants who were GADA negative.”

“Our findings have clear implications for clinical practice. The T1D GRS represents a novel clinical test that can be used to enhance the prognostic value of GADA testing. For predicting future insulin requirement in patients with apparent type 2 diabetes who are GADA positive, T1D GRS may be clinically useful and can be used as an additional test in the screening process. However, in patients with type 2 diabetes who are GADA negative, there is no benefit gained from genetic testing. This is unsurprising, as the prevalence of underlying autoimmunity in patients with a clinical phenotype of type 2 diabetes who are GADA negative is likely to be extremely low; therefore, most GADA-negative participants with high T1D GRS will have nonautoimmune diabetes. The use of this two-step testing approach may facilitate a precision medicine approach to patients with apparent type 2 diabetes; patients who are likely to progress rapidly are identified for targeted management, which may include increased monitoring, early therapy intensification, and/or interventions aimed at slowing progression (36,37).

The costs of analyzing the T1D GRS are relatively modest and may fall further, as genetic testing is rapidly becoming less expensive (38). […] In conclusion, a T1D GRS alters the clinical implications of a positive GADA test in patients with clinical type 2 diabetes and is independent of and additive to clinical features. This therefore represents a novel test for identifying patients with rapid progression in this population.”

iii. Retinopathy and RAAS Activation: Results From the Canadian Study of Longevity in Type 1 Diabetes.

“Diabetic retinopathy is the most common cause of preventable blindness in individuals ages 20–74 years and is the most common vascular complication in type 1 and type 2 diabetes (13). On the basis of increasing severity, diabetic retinopathy is classified into nonproliferative diabetic retinopathy (NPDR), defined in early stages by the presence of microaneurysms, retinal vascular closure, and alteration, or proliferative diabetic retinopathy (PDR), defined by the growth of new aberrant blood vessels (neovascularization) susceptible to hemorrhage, leakage, and fibrosis (4). Diabetic macular edema (DME) can be present at any stage of retinopathy and is characterized by increased vascular permeability leading to retinal thickening.

Important risk factors for the development of retinopathy continue to be chronic hyperglycemia, hyperlipidemia, hypertension, and diabetes duration (5,6). Given the systemic nature of these risk factors, cooccurrence of retinopathy with other vascular complications is common in patients with diabetes.”

“A key pathway implicated in diabetes-related small-vessel disease is overactivation of neurohormones. Activation of the neurohormonal renin-angiotensin-aldosterone system (RAAS) pathway predominates in diabetes in response to hyperglycemia and sodium retention. The RAAS plays a pivotal role in regulating systemic BP through vasoconstriction and fluid-electrolyte homeostasis. At the tissue level, angiotensin II (ANGII), the principal mediator of the RAAS, is implicated in fibrosis, oxidative stress, endothelial damage, thrombosis, inflammation, and vascular remodeling. Of note, systemic RAAS blockers reduce the risk of progression of eye disease but not DKD [Diabetic Kidney Disease, US] in adults with type 1 diabetes with normoalbuminuria (12).

Several longitudinal epidemiologic studies of diabetic retinopathy have been completed in type 1 diabetes; however, few have studied the relationships between eye, nerve, and renal complications and the influence of RAAS activation after prolonged duration (≥50 years) in adults with type 1 diabetes. As a result, less is known about mechanisms that persist in diabetes-related microvascular complications after long-standing diabetes. Accordingly, in this cross-sectional analysis from the Canadian Study of Longevity in Type 1 Diabetes involving adults with type 1 diabetes for ≥50 years, our aims were to phenotype retinopathy stage and determine associations between the presence of retinopathy and other vascular complications. In addition, we examined the relationship between retinopathy stage and renal and systemic hemodynamic function, including arterial stiffness, at baseline and dynamically after RAAS activation with an infusion of exogenous ANGII.”

“Of the 75 participants, 12 (16%) had NDR [no diabetic retinopathy], 24 (32%) had NPDR, and 39 (52%) had PDR […]. At baseline, those with NDR had lower mean HbA1c compared with those with NPDR and PDR (7.4 ± 0.7% and 7.5 ± 0.9%, respectively; P for trend = 0.019). Of note, those with more severe eye disease (PDR) had lower systolic and diastolic BP values but a significantly higher urine albumin-to-creatine ratio (UACR) […] compared with those with less severe eye disease (NPDR) or with NDR despite higher use of RAAS inhibitors among those with PDR compared with NPDR or NDR. History of cardiovascular and peripheral vascular disease history was significantly higher in participants with PDR (33.3%) than in those with NPDR (8.3%) or NDR (0%). Diabetic sensory polyneuropathy was prevalent across all groups irrespective of retinopathy status but was numerically higher in the PDR group (95%) than in the NPDR (86%) or NDR (75%) groups. No significant differences were observed in retinal thickness across the three groups.”

One quick note: This was mainly an eye study, but some of the other figures here are well worth taking note of. 3 out of 4 people in the supposedly low-risk group without eye complications had sensory polyneuropathy after 50 years of diabetes.

Conclusions

Hyperglycemia contributes to the pathogenesis of diabetic retinopathy through multiple interactive pathways, including increased production of advanced glycation end products, IGF-I, vascular endothelial growth factor, endothelin, nitric oxide, oxidative damage, and proinflammatory cytokines (2933). Overactivation of the RAAS in response to hyperglycemia also is implicated in the pathogenesis of diabetes-related complications in the retina, nerves, and kidney and is an important therapeutic target in type 1 diabetes. Despite what is known about these underlying pathogenic mechanisms in the early development of diabetes-related complications, whether the same mechanisms are active in the setting of long-standing type 1 diabetes is not known. […] In this study, we observed that participants with PDR were more likely to be taking RAAS inhibitors, to have a higher frequency of cardiovascular or peripheral vascular disease, and to have higher UACR levels, likely reflecting the higher overall risk profile of this group. Although it is not possible to determine why some patients in this cohort developed PDR while others did not after similar durations of type 1 diabetes, it seems unlikely that glycemic control alone is sufficient to fully explain the observed between-group differences and differing vascular risk profiles. Whereas the NDR group had significantly lower mean HbA1c levels than the NPDR and PDR groups, differences between participants with NPDR and those with PDR were modest. Accordingly, other factors, such as differences in vascular function, neurohormones, growth factors, genetics, and lifestyle, may play a role in determining retinopathy severity at the individual level.

The association between retinopathy and risk for DKD is well established in diabetes (34). In the setting of type 2 diabetes, patients with high levels of UACR have twice the risk of developing diabetic retinopathy than those with normal UACR levels. For example, Rodríguez-Poncelas et al. (35) demonstrated that impaired renal function is linked with increased diabetic retinopathy risk. Consistent with these studies and others, the PDR group in this Canadian Study of Longevity in Type 1 Diabetes demonstrated significantly higher UACR, which is associated with an increased risk of DKD progression, illustrating that the interaction between eye and kidney disease progression also may exist in patients with long-standing type 1 diabetes. […] In conclusion, retinopathy was prevalent after prolonged type 1 diabetes duration, and retinopathy severity associated with several measures of neuropathy and with higher UACR. Differential exaggerated responses to RAAS activation in the peripheral vasculature of the PDR group highlights that even in the absence of DKD, neurohormonal abnormalities are likely still operant, and perhaps accentuated, in patients with PDR even after long-standing type 1 diabetes duration.”

iv. Clinical and MRI Features of Cerebral Small-Vessel Disease in Type 1 Diabetes.

“Type 1 diabetes is associated with a fivefold increased risk of stroke (1), with cerebral small-vessel disease (SVD) as the most common etiology (2). Cerebral SVD in type 1 diabetes, however, remains scarcely investigated and is challenging to study in vivo per se owing to the size of affected vasculature (3); instead, MRI signs of SVD are studied. In this study, we aimed to assess the prevalence of cerebral SVD in subjects with type 1 diabetes compared with healthy control subjects and to characterize diabetes-related variables associated with SVD in stroke-free people with type 1 diabetes.”

RESEARCH DESIGN AND METHODS This substudy was cross-sectional in design and included 191 participants with type 1 diabetes and median age 40.0 years (interquartile range 33.0–45.1) and 30 healthy age- and sex-matched control subjects. All participants underwent clinical investigation and brain MRIs, assessed for cerebral SVD.

RESULTS Cerebral SVD was more common in participants with type 1 diabetes than in healthy control subjects: any marker 35% vs. 10% (P = 0.005), cerebral microbleeds (CMBs) 24% vs. 3.3% (P = 0.008), white matter hyperintensities 17% vs. 6.7% (P = 0.182), and lacunes 2.1% vs. 0% (P = 1.000). Presence of CMBs was independently associated with systolic blood pressure (odds ratio 1.03 [95% CI 1.00–1.05], P = 0.035).”

Conclusions

Cerebral SVD is more common in participants with type 1 diabetes than in healthy control subjects. CMBs especially are more prevalent and are independently associated with hypertension. Our results indicate that cerebral SVD starts early in type 1 diabetes but is not explained solely by diabetes-related vascular risk factors or the generalized microvascular disease that takes place in diabetes (7).

There are only small-scale studies on cerebral SVD, especially CMBs, in type 1 diabetes. Compared with the current study, one study with similar diabetes characteristics (i.e., diabetes duration, glycemic control, and blood pressure levels) as in the current study, but lacking a control population, showed a higher prevalence of WMHs, with more than half of the participants affected, but similar prevalence of lacunes and lower prevalence of CMBs (8). In another study, including 67 participants with type 1 diabetes and 33 control subjects, there was no difference in WMH prevalence but a higher prevalence of CMBs in participants with type 1 diabetes and retinopathy compared with control subjects (9). […] In type 1 diabetes, albuminuria and systolic blood pressure independently increase the risk for both ischemic and hemorrhagic stroke (12). […] We conclude that cerebral SVD is more common in subjects with type 1 diabetes than in healthy control subjects. Future studies will focus on longitudinal development of SVD in type 1 diabetes and the associations with brain health and cognition.”

v. The Legacy Effect in Type 2 Diabetes: Impact of Early Glycemic Control on Future Complications (The Diabetes & Aging Study).

“In the U.S., an estimated 1.4 million adults are newly diagnosed with diabetes every year and present an important intervention opportunity for health care systems. In patients newly diagnosed with type 2 diabetes, the benefits of maintaining an HbA1c <7.0% (<53 mmol/mol) are well established. The UK Prospective Diabetes Study (UKPDS) found that a mean HbA1c of 7.0% (53 mmol/mol) lowers the risk of diabetes-related end points by 12–32% compared with a mean HbA1c of 7.9% (63 mmol/mol) (1,2). Long-term observational follow-up of this trial revealed that this early glycemic control has durable effects: Reductions in microvascular events persisted, reductions in cardiovascular events and mortality were observed 10 years after the trial ended, and HbA1c values converged (1). Similar findings were observed in the Diabetes Control and Complications Trial (DCCT) in patients with type 1 diabetes (24). These posttrial observations have been called legacy effects (also metabolic memory) (5), and they suggest the importance of early glycemic control for the prevention of future complications of diabetes. Although these clinical trial long-term follow-up studies demonstrated legacy effects, whether legacy effects exist in real-world populations, how soon after diabetes diagnosis legacy effects may begin, or for what level of glycemic control legacy effects may exist are not known.

In a previous retrospective cohort study, we found that patients with newly diagnosed diabetes and an initial 10-year HbA1c trajectory that was unstable (i.e., changed substantially over time) had an increased risk for future microvascular events, even after adjusting for HbA1c exposure (6). In the same cohort population, this study evaluates associations between the duration and intensity of glycemic control immediately after diagnosis and the long-term incidence of future diabetic complications and mortality. We hypothesized that a glycemic legacy effect exists in real-world populations, begins as early as the 1st year after diabetes diagnosis, and depends on the level of glycemic exposure.”

RESEARCH DESIGN AND METHODS This cohort study of managed care patients with newly diagnosed type 2 diabetes and 10 years of survival (1997–2013, average follow-up 13.0 years, N = 34,737) examined associations between HbA1c <6.5% (<48 mmol/mol), 6.5% to <7.0% (48 to <53 mmol/mol), 7.0% to <8.0% (53 to <64 mmol/mol), 8.0% to <9.0% (64 to <75 mmol/mol), or ≥9.0% (≥75 mmol/mol) for various periods of early exposure (0–1, 0–2, 0–3, 0–4, 0–5, 0–6, and 0–7 years) and incident future microvascular (end-stage renal disease, advanced eye disease, amputation) and macrovascular (stroke, heart disease/failure, vascular disease) events and death, adjusting for demographics, risk factors, comorbidities, and later HbA1c.

RESULTS Compared with HbA1c <6.5% (<48 mmol/mol) for the 0-to-1-year early exposure period, HbA1c levels ≥6.5% (≥48 mmol/mol) were associated with increased microvascular and macrovascular events (e.g., HbA1c 6.5% to <7.0% [48 to <53 mmol/mol] microvascular: hazard ratio 1.204 [95% CI 1.063–1.365]), and HbA1c levels ≥7.0% (≥53 mmol/mol) were associated with increased mortality (e.g., HbA1c 7.0% to <8.0% [53 to <64 mmol/mol]: 1.290 [1.104–1.507]). Longer periods of exposure to HbA1c levels ≥8.0% (≥64 mmol/mol) were associated with increasing microvascular event and mortality risk.

CONCLUSIONS Among patients with newly diagnosed diabetes and 10 years of survival, HbA1c levels ≥6.5% (≥48 mmol/mol) for the 1st year after diagnosis were associated with worse outcomes. Immediate, intensive treatment for newly diagnosed patients may be necessary to avoid irremediable long-term risk for diabetic complications and mortality.”

Do note that the effect sizes here are very large and this stuff seems really quite important. Judging from the results of this study, if you’re newly diagnosed and you only obtain a HbA1c of say, 7.3% in the first year, that may translate into a close to 30% increased risk of death more than 10 years into the future, compared to a scenario of an HbA1c of 6.3%. People who did not get their HbA1c measured within the first 3 months after diagnosis had a more than 20% increased risk of mortality during the study period. This seems like critical stuff to get right.

vi. Event Rates and Risk Factors for the Development of Diabetic Ketoacidosis in Adult Patients With Type 1 Diabetes: Analysis From the DPV Registry Based on 46,966 Patients.

“Diabetic ketoacidosis (DKA) is a life-threatening complication of type 1 diabetes mellitus (T1DM) that results from absolute insulin deficiency and is marked by acidosis, ketosis, and hyperglycemia (1). Therefore, prevention of DKA is one goal in T1DM care, but recent data indicate increased incidence (2).

For adult patients, only limited data are available on rates and risk factors for development of DKA, and this complication remains epidemiologically poorly characterized. The Diabetes Prospective Follow-up Registry (DPV) has followed patients with diabetes from 1995. Data for this study were collected from 2000 to 2016. Inclusion criteria were diagnosis of T1DM, age at diabetes onset ≥6 months, patient age at follow-up ≥18 years, and diabetes duration ≥1 year to exclude DKA at manifestation. […] In total, 46,966 patients were included in this study (average age 38.5 years [median 21.2], 47.6% female). The median HbA1c was 7.7% (61 mmol/mol), median diabetes duration was 13.6 years, and 58.3% of the patients were treated in large diabetes centers.

On average, 2.5 DKA-related hospital admissions per 100 patient-years (PY) were observed (95% CI 2.1–3.0). The rate was highest in patients aged 18–30 years (4.03/100 PY) and gradually declined with increasing age […] No significant differences between males (2.46/100 PY) and females (2.59/100 PY) were found […] Patients with HbA1c levels <7% (53 mmol/mol) had significantly fewer DKA admissions than patients with HbA1c ≥9% (75 mmol/mol) (0.88/100 PY vs. 6.04/100 PY; P < 0.001)”

“Regarding therapy, use of an insulin pump (continuous subcutaneous insulin infusion [CSII]) was not associated with higher DKA rates […], while patients aged 31–50 years on CSII showed lower rates than patients using multiple daily injections (2.21 vs. 3.12/100 PY; adjusted P < 0.05) […]. Treatment in a large center was associated with lower DKA-related hospital admissions […] In both adults and children, poor metabolic control was the strongest predictor of hospital admission due to DKA. […] In conclusion, the results of this study identify patients with T1DM at risk for DKA (high HbA1c, diabetes duration 5–10 years, migrants, age 30 years and younger) in real-life diabetes care. These at-risk individuals may need specific attention since structured diabetes education has been demonstrated to specifically reduce and prevent this acute complication.”

August 13, 2019 Posted by | Cardiology, Diabetes, Genetics, Immunology, Medicine, Molecular biology, Nephrology, Neurology, Ophthalmology, Studies | Leave a comment

A few diabetes papers of interest

i. The dynamic origins of type 1 diabetes.

“Over a century ago, there was diabetes and only diabetes. Subsequently, diabetes came to be much more discretely defined (1) by age at onset (childhood or adult onset), clinical phenotype (lean or obese), treatment (insulin dependent or not insulin dependent), and, more recently, immune genotype (type 1 or type 2 diabetes). Although these categories broadly describe groups, they are often insufficient to categorize specific individuals, such as children having non–insulin-dependent diabetes and adults having type 1 diabetes (T1D) even when not requiring insulin. Indeed, ketoacidosis at presentation can be a feature of either T1D or type 2 diabetes. That heterogeneity extends to the origins and character of both major types of diabetes. In this issue of Diabetes Care, Redondo et al. (2) leverage the TrialNet study of subjects with a single diabetes-associated autoantibody at screening in order to explore factors determining progression to multiple autoantibodies and, subsequently, the pathogenesis of T1D.

T1D is initiated by presumed nongenetic event(s) operating in children with potent genetic susceptibility. But there is substantial heterogeneity even within the origins of this disease. Those nongenetic events evoke different autoantibodies such that T1D patients with insulin autoantibodies (IAA) have different features from those with GAD autoantibodies (GADA) (3,4). The former, in contrast with the latter, are younger both at seroconversion and at development of clinical diabetes, the two groups having different genetic risk and those with IAA having greater insulin secretory loss […]. These observations hint at distinct disease-associated networks leading to T1D, perhaps induced by distinct nongenetic events. Such disease-associated pathways could operate in unison, especially in children with T1D, who often have multiple autoantibodies. […]

Genetic analyses of autoimmune diseases suggest that only a small number of pathways contribute to disease risk. These pathways include NF-κB signaling, T-cell costimulation, interleukin-2, and interleukin-21 pathways and type 1 interferon antiviral responses (5,6). T1D shares most risk loci with celiac disease and rheumatoid arthritis (5), while paradoxically most risk loci shared with inflammatory bowel disease are protective or involve different haplotypes at the same locus. […] Events leading to islet autoimmunity may be encountered very early in life and invoke disease risk or disease protection (4,7) […]. Islet autoantibodies rarely appear before age 6 months, and among children with a family history of T1D there are two peaks for autoantibody seroconversion (3,4), the first for IAA at approximately age 1–2 years, while GADA-restricted autoimmunity develops after age 3 years up to adolescence, with a peak at about age 11 years”

“The precise nature of […] disease-associated nongenetic events remains unclear, but knowledge of the disease heterogeneity (1,9) has cast light on their character. Nongenetic events are implicated in increasing disease incidence, disease discordance even between identical twins, and geographical variation; e.g., Finland has 100-fold greater childhood T1D incidence than China (9,10). That effect likely increases with older age at onset […] disease incidence in Finland is sixfold greater than in an adjacent, relatively impoverished Russian province, despite similar racial origins and frequencies of high-risk HLA DQ genotypes […] Viruses, especially enteroviruses, and dietary factors have been invoked (1215). The former have been implicated because of the genetic association with antiviral interferon networks, seasonal pattern of autoantibody conversion, seroconversion being associated with enterovirus infections, and protection from seroconversion by maternal gestational respiratory infection, while respiratory infections even in the first year of life predispose to seroconversion (14) […]. Dietary factors also predispose to seroconversion and include the time of introduction of solid foods and the use of vitamin C and vitamin D (13,15). The Diabetes Autoimmunity Study in the Young (DAISY) found that early exposure to solid food (1–3 months of age) and vitamin C and late exposure to vitamin D and gluten (after 6 and 9 months of age, respectively) are T1D risk factors, leading the researchers to suggest that genetically at-risk children should have solid foods introduced at about 4 months of age with a diet high in dairy and fruit (13).” [my bold, US]

“This TCF7L2 locus is of particular interest in the context of T1D (9) as it is usually seen as the major type 2 diabetes signal worldwide. The rs7903146 SNP optimally captures that TCF7L2 disease association and is likely the causal variant. Intriguingly, this locus is associated, in some populations, with those adult-onset autoimmune diabetes patients with GADA alone who masquerade as having type 2 diabetes, since they initially do not require insulin therapy, and also markedly increases the diabetes risk in cystic fibrosis patients. One obvious explanation for these associations is that adult-onset autoimmune diabetes is simply a heterogeneous disease, an admixture of both T1D and type 2 diabetes (9), in which shared genes alter the threshold for diabetes. […] A high proportion of T1D cases present in adulthood (17,18), likely more than 50%, and many do not require insulin initially. The natural history, phenotype, and metabolic changes in adult-onset diabetes with GADA resemble a separate cluster of cases with type 2 diabetes but without GADA, which together constitute up to 24% of adult-onset diabetes (19). […] Knowledge of heterogeneity enables understanding of disease processes. In particular, identification of distinct pathways to clinical diabetes offers the possibility of defining distinct nongenetic events leading to T1D and, by implication, modulating those events could limit or eliminate disease progression. There is a growing appreciation that the two major types of diabetes may share common etiopathological factors. Just as there are a limited number of genes and pathways contributing to autoimmunity risk, there may also be a restricted number of pathways contributing to β-cell fragility.”

ii. The Association of Severe Diabetic Retinopathy With Cardiovascular Outcomes in Long-standing Type 1 Diabetes: A Longitudinal Follow-up.

OBJECTIVE It is well established that diabetic nephropathy increases the risk of cardiovascular disease (CVD), but how severe diabetic retinopathy (SDR) impacts this risk has yet to be determined.

RESEARCH DESIGN AND METHODS The cumulative incidence of various CVD events, including coronary heart disease (CHD), peripheral artery disease (PAD), and stroke, retrieved from registries, was evaluated in 1,683 individuals with at least a 30-year duration of type 1 diabetes drawn from the Finnish Diabetic Nephropathy Study (FinnDiane).”

RESULTS During 12,872 person-years of follow-up, 416 incident CVD events occurred. Even in the absence of DKD [Diabetic Kidney Disease], SDR increased the risk of any CVD (hazard ratio 1.46 [95% CI 1.11–1.92]; P < 0.01), after adjustment for diabetes duration, age at diabetes onset, sex, smoking, blood pressure, waist-to-hip ratio, history of hypoglycemia, and serum lipids. In particular, SDR alone was associated with the risk of PAD (1.90 [1.13–3.17]; P < 0.05) and CHD (1.50 [1.09–2.07; P < 0.05) but not with any stroke. Moreover, DKD increased the CVD risk further (2.85 [2.13–3.81]; P < 0.001). […]

CONCLUSIONS SDR alone, even without DKD, increases cardiovascular risk, particularly for PAD, independently of common cardiovascular risk factors in long-standing type 1 diabetes. More remains to be done to fully understand the link between SDR and CVD. This knowledge could help combat the enhanced cardiovascular risk beyond currently available regimens.”

“The 15-year cumulative incidence of any CVD in patients with and without SDR was 36.8% (95% CI 33.4–40.1) and 27.3% (23.3–31.0), respectively (P = 0.0004 for log-rank test) […] Patients without DKD and SDR at baseline had 4.0-fold (95% CI 3.3–4.7) increased risk of CVD compared with control subjects without diabetes up to 70 years of age […]. Intriguingly, after this age, the CVD incidence was similar to that in the matched control subjects (SIR 0.9 [95% CI 0.3–1.9]) in this subgroup of patients with diabetes. However, in patients without DKD but with SDR, the CVD risk was still increased after the patients had reached 70 years of age (SIR 3.4 [95% CI 1.8–6.2]) […]. Of note, in patients with both DKD and SDR, the CVD burden was high already at young ages.”

“This study highlights the role of SDR on a complete range of CVD outcomes in a large sample of patients with long-standing T1D and longitudinal follow-up. We showed that SDR alone, without concomitant DKD, increases the risk of macrovascular disease, independently of the traditional risk factors. The risk is further increased in case of accompanying DKD, especially if SDR is present together with DKD. Findings from this large and well-characterized cohort of patients have a direct impact on clinical practice, emphasizing the importance of regular screening for SDR in individuals with T1D and intensive multifactorial interventions for CVD prevention throughout their life span.

This study also confirms and complements previous data on the continuum of diabetic vascular disease, by which microvascular and macrovascular disease do not seem to be separate diseases, but rather interconnected (10,12,18). The link is most obvious for DKD, which clearly emerges as a major predictor of cardiovascular morbidity and mortality (2,24,25). The association of SDR with CVD is less clear. However, our recent cross-sectional study with the Joslin Medalist Study showed that the CVD risk was in fact increased in patients with SDR on top of DKD compared with DKD alone (19). In the present longitudinal study, we were able to extend those results also to show that SDR alone, without DKD and after the adjustment for other traditional risk factors, increases CVD risk substantially. SDR further increases CVD risk in case DKD is present as well. In addition, the role of SDR as an independent CVD risk predictor is also supported by our data using albuminuria as a marker of DKD. This is important because albuminuria is a known predictor of diabetic retinopathy progression (26) as well as a recognized biomarker for CVD.”

“A novel finding is that, independently of any signs of DKD, the risk of PAD is increased twofold in the presence of SDR. Although this association has recently been highlighted in individuals with type 2 diabetes (10,29), the data in T1D are scarce (16,30). Notably, the previous studies mostly lack adjustments for DKD, the major predictor of mortality in patients with shorter diabetes duration. Both complications, besides sharing some conventional cardiovascular risk factors, may be linked by additional pathological processes involving changes in the microvasculature in both the retina and the vasa vasorum of the conductance vessels (31). […] Patients with T1D duration of >30 years face a continuously increased CVD risk that is further increased by the occurrence of advanced PDR. Therefore, by examining the retina, additional insight into individual CVD risk is gained and can guide the clinician to a more tailored approach to CVD prevention. Moreover, our findings suggest that the link between SDR and CVD is at least partially independent of traditional risk factors, and the mechanism behind the phenomenon warrants further research, aiming to find new therapies to alleviate the CVD burden more efficiently.”

The model selection method employed in the paper is far from optimal [“Variables for the model were chosen based on significant univariable associations.” – This is not the way to do things!], but regardless these are interesting results.

iii. Fasting Glucose Variability in Young Adulthood and Cognitive Function in Middle Age: The Coronary Artery Risk Development in Young Adults (CARDIA) Study.

“Individuals with type 2 diabetes (T2D) have 50% greater risk for the development of neurocognitive dysfunction relative to those without T2D (13). The American Diabetes Association recommends screening for the early detection of cognitive impairment for adults ≥65 years of age with diabetes (4). Coupled with the increasing prevalence of prediabetes and diabetes, this calls for better understanding of the impact of diabetes on cerebral structure and function (5,6). Among older individuals with diabetes, higher intraindividual variability in glucose levels around the mean is associated with worse cognition and the development of Alzheimer disease (AD) (7,8). […] Our objectives were to characterize fasting glucose (FG) variability during young adulthood before the onset of diabetes and to assess whether such variability in FG is associated with cognitive function in middle adulthood. We hypothesized that a higher variability of FG during young adulthood would be associated with a lower level of cognitive function in midlife compared with lower FG variability.”

“We studied 3,307 CARDIA (Coronary Artery Risk Development in Young Adults) Study participants (age range 18–30 years and enrolled in 1985–1986) at baseline and calculated two measures of long-term glucose variability: the coefficient of variation about the mean FG (CV-FG) and the absolute difference between successive FG measurements (average real variability [ARV-FG]) before the onset of diabetes over 25 and 30 years of follow-up. Cognitive function was assessed at years 25 (2010–2011) and 30 (2015–2016) with the Digit Symbol Substitution Test (DSST), Rey-Auditory Verbal Learning Test (RAVLT), Stroop Test, Montreal Cognitive Assessment, and category and letter fluency tests. We estimated the association between glucose variability and cognitive function test score with adjustment for clinical and behavioral risk factors, mean FG level, change in FG level, and diabetes development, medication use, and duration.

RESULTS After multivariable adjustment, 1-SD increment of CV-FG was associated with worse cognitive scores at year 25: DSST, standardized regression coefficient −0.95 (95% CI −1.54, −0.36); RAVLT, −0.14 (95% CI −0.27, −0.02); and Stroop Test, 0.49 (95% CI 0.04, 0.94). […] We did not find evidence for effect modification by race or sex for any variability-cognitive function association”

CONCLUSIONS Higher intraindividual FG variability during young adulthood below the threshold of diabetes was associated with worse processing speed, memory, and language fluency in midlife independent of FG levels. […] In this cohort of black and white adults followed from young adulthood into middle age, we observed that greater intraindividual variability in FG below a diabetes threshold was associated with poorer cognitive function independent of behavioral and clinical risk factors. This association was observed above and beyond adjustment for concurrent glucose level; change in FG level during young adulthood; and diabetes status, duration, and medication use. Intraindividual glucose variability as determined by CV was more strongly associated with cognitive function than was absolute average glucose variability.”

iv. Maternal Antibiotic Use During Pregnancy and Type 1 Diabetes in Children — A National Prospective Cohort Study. It is important that papers like these get published and read, even if the results may not sound particularly exciting:

“Prenatal prescription of antibiotics is common but may perturb the composition of the intestinal microbiota in the offspring. In childhood the latter may alter the developing immune system to affect the pathogenesis of type 1 diabetes (1). Previous epidemiological studies reported conflicting results regarding the association between early exposure to antibiotics and childhood type 1 diabetes (2,3). Here we investigated the association in a Danish register setting.

The Danish National Birth Cohort (DNBC) provided data from 100,418 pregnant women recruited between 1996 and 2002 and their children born between 1997 and 2003 (n = 96,840). The women provided information on exposures during and after pregnancy. Antibiotic prescription during pregnancy was obtained from the Danish National Prescription Registry (anatomical therapeutic chemical code J01) [it is important to note that: “In Denmark, purchasing antibiotics requires a prescription, and all purchases are registered at the Danish National Prescription Registry”], and type 1 diabetes diagnoses (diagnostic codes DE10 and DE14) during childhood and adolescence were obtained from the Danish National Patient Register. The children were followed until 2014 (mean follow-up time 14.3 years [range 11.5–18.4 years, SD 1.4]).”

“A total of 336 children developed type 1 diabetes during follow-up. Neither overall exposure (hazard ratio [HR] 0.90; 95% CI 0.68–1.18), number of courses (HR 0.36–0.97[…]), nor trimester-specific exposure (HR 0.81–0.89 […]) of antibiotics in utero was associated with childhood diabetes. Moreover, exposure to specific types of antibiotics in utero did not change the risk of childhood type 1 diabetes […] This large prospective Danish cohort study demonstrated that maternal use of antibiotics during pregnancy was not associated with childhood type 1 diabetes. Thus, the results from this study do not support a revision of the clinical recommendations on treatment with antibiotics during pregnancy.”

v. Decreasing Cumulative Incidence of End-Stage Renal Disease in Young Patients With Type 1 Diabetes in Sweden: A 38-Year Prospective Nationwide Study.

“Diabetic nephropathy is a devastating complication to diabetes. It can lead to end-stage renal disease (ESRD), which demands renal replacement therapy (RRT) with dialysis or kidney transplantation. In addition, diabetic nephropathy is associated with increased risk of cardiovascular morbidity and mortality (1,2). As a nation, Sweden, next to Finland, has the highest incidence of type 1 diabetes in the world (3), and the incidence of childhood-onset diabetes is increasing globally (4,5). The incidence of ESRD caused by diabetic nephropathy in these Nordic countries is fairly low as shown in recent studies, 3–8% at maximum 30 years’ of diabetes duration (6,7). This is to be compared with studies from Denmark in the 1980s that showed a cumulative incidence of diabetic nephropathy of 41% at 40 years of diabetes duration. Older, hospital-based cohort studies found that the incidence of persistent proteinuria seemed to peak at 25 years of diabetes duration; after that, the incidence levels off (8,9). This implies the importance of genetic susceptibility as a risk factor for diabetic nephropathy, which has also been indicated in recent genome-wide scan studies (10,11). Still, modifiable factors such as metabolic control are clearly of major importance in the development of diabetic nephropathy (1215). Already in 1994, a decreasing incidence of diabetic nephropathy was seen in a hospital-based study in Sweden, and the authors concluded that this was mainly driven by better metabolic control (16). Young age at onset of diabetes has previously been found to protect, or postpone, the development of ESRD caused by diabetic nephropathy, while diabetes onset at older ages is associated with increased risk (7,9,17). In a previous study, we found that age at onset of diabetes affects men and women differently (7). Earlier studies have indicated a male predominance (8,18), while our previous study showed that the incidence of ESRD was similar in men and women with diabetes onset before 20 years of age, but with diabetes onset after 20 years of age, men had increased risk of developing ESRD compared with women. The current study analyzes the incidence of ESRD due to type 1 diabetes, and changes over time, in a large Swedish population-based cohort with a maximum follow-up of 38 years.”

“Earlier studies have shown that it takes ∼15 years to develop persistent proteinuria and another 10 to proceed to ESRD (9,25). In the current study population, no patients developed ESRD because of type 1 diabetes at a duration <14 years; thus only patients with diabetes duration of ≥14 years were included in the study. […] A total of 18,760 unique patients were included in the study: 10,560 (56%) men and 8,200 (44%) women. The mean age at the end of the study was somewhat lower for women, 38.9 years, compared with 40.2 years for men. Women tend to develop type 1 diabetes about a year earlier than men: mean age 15.0 years for women compared with 16.5 years for men. There was no difference regarding mean diabetes duration between men and women in the study (23.8 years for women and 23.7 years for men). A total of 317 patients had developed ESRD due to diabetes. The maximum diabetes duration was 38.1 years for patients in the SCDR and 32.6 years for the NDR and the DISS. The median time from onset of diabetes to ESRD was 22.9 years (minimum 14.1 and maximum 36.6). […] At follow-up, 77 patients with ESRD and 379 without ESRD had died […]. The risk of dying during the course of the study was almost 12 times higher among the ESRD patients (HR 11.9 [95% CI 9.3–15.2]) when adjusted for sex and age. Males had almost twice as high a risk of dying as female patients (HR 1.7 [95% CI 1.4–2.1]), adjusted for ESRD and age.”

“The overall incidence rate of ESRD during 445,483 person-years of follow-up was 0.71 per 1,000 person-years. […] The incidence rate increases with diabetes duration. For patients with diabetes onset at 0–9 and 10–19 years of age, there was an increase in incidence up to 36 years of duration; at longer durations, the number of cases is too small and results must be interpreted with caution. With diabetes onset at 20–34 years of age the incidence rate increases until 25 years of diabetes duration, and then a decrease can be observed […] In comparison of different time periods, the risk of developing ESRD was lower in patients with diabetes onset in 1991–2001 compared with onset in 1977–1984 (HR 3.5 [95% CI 2.3–5.3]) and 1985–1990 (HR 2.6 [95% CI 1.7–3.8]), adjusted for age at follow-up and sex. […] The lowest risk of developing ESRD was found in the group with onset of diabetes before the age of 10 years — both for males and females […]. With this group as reference, males diagnosed with diabetes at 10–19 or 20–34 years of age had increased risk of ESRD (HR 2.4 [95% CI 1.6–3.5] and HR 2.2 [95% CI 1.4–3.3]), respectively. For females, the risk of developing ESRD was also increased with diabetes onset at 10–19 years of age (HR 2.4 [95% CI 1.5–3.6]); however, when diabetes was diagnosed after the age of 20 years, the risk of developing ESRD was not increased compared with an early onset of diabetes (HR 1.4 [95% CI 0.8–3.4]).”

“By combining data from the SCDR, DISS, and NDR registers and identifying ESRD cases via the SRR, we have included close to all patients with type 1 diabetes in Sweden with diabetes duration >14 years who developed ESRD since 1991. The cumulative incidence of ESRD in this study is low: 5.6% (5.9% and 5.3% for males and females, respectively) at maximum 38 years of diabetes duration. For the first time, we could see a clear decrease in ESRD incidence in Sweden by calendar year of diabetes onset. The results are in line with a recent study from Norway that reported a modest incidence of 5.3% after 40 years of diabetes duration (27). In the current study, we found a decrease in the incidence rate after 25 years of diabetes duration in the group with diabetes onset at 20–34 years. With age at onset of diabetes 0–9 or 10–19 years, the ESRD incidence rate increases until 35 years of diabetes duration, but owing to the limited number of patients with longer duration we cannot determine whether the peak incidence has been reached or not. We can, however, conclude that the onset of ESRD has been postponed at least 10 years compared with that in older prospective cohort studies (8,9). […] In conclusion, this large population-based study shows a low incidence of ESRD in Swedish patients with onset of type 1 diabetes after 1977 and an encouraging decrease in risk of ESRD, which is probably an effect of improved diabetes care. We confirm that young age at onset of diabetes protects against, or prolongs, the time until development of severe complications.”

vi. Hypoglycemia and Incident Cognitive Dysfunction: A Post Hoc Analysis From the ORIGIN Trial. Another potentially important negative result, this one related to the link between hypoglycemia and cognitive impairment:

“Epidemiological studies have reported a relationship between severe hypoglycemia, cognitive dysfunction, and dementia in middle-aged and older people with type 2 diabetes. However, whether severe or nonsevere hypoglycemia precedes cognitive dysfunction is unclear. Thus, the aim of this study was to analyze the relationship between hypoglycemia and incident cognitive dysfunction in a group of carefully followed patients using prospectively collected data in the Outcome Reduction with Initial Glargine Intervention (ORIGIN) trial.”

“This prospective cohort analysis of data from a randomized controlled trial included individuals with dysglycemia who had additional cardiovascular risk factors and a Mini-Mental State Examination (MMSE) score ≥24 (N = 11,495). Severe and nonsevere hypoglycemic events were collected prospectively during a median follow-up time of 6.2 years. Incident cognitive dysfunction was defined as either reported dementia or an MMSE score of <24. The hazard of at least one episode of severe or nonsevere hypoglycemia for incident cognitive dysfunction (i.e., the dependent variable) from the time of randomization was estimated using a Cox proportional hazards model after adjusting for baseline cardiovascular disease, diabetes status, treatment allocation, and a propensity score for either form of hypoglycemia.

RESULTS This analysis did not demonstrate an association between severe hypoglycemia and incident cognitive impairment either before (hazard ratio [HR] 1.16; 95% CI 0.89, 1.52) or after (HR 1.00; 95% CI 0.76, 1.31) adjusting for the severe hypoglycemia propensities. Conversely, nonsevere hypoglycemia was inversely related to incident cognitive impairment both before (HR 0.59; 95% CI 0.52, 0.68) and after (HR 0.58; 95% CI 0.51, 0.67) adjustment.

CONCLUSIONS Hypoglycemia did not increase the risk of incident cognitive dysfunction in 11,495 middle-aged individuals with dysglycemia. […] These findings provide no support for the hypothesis that hypoglycemia causes long-term cognitive decline and are therefore reassuring for patients and their health care providers.”

vii. Effects of Severe Hypoglycemia on Cardiovascular Outcomes and Death in the Veterans Affairs Diabetes Trial.

“The VADT was a large randomized controlled trial aimed at determining the effects of intensive treatment of T2DM in U.S. veterans (9). In the current study, we examine predictors and consequences of severe hypoglycemia within the VADT and report several key findings. First, we identified risk factors for severe hypoglycemia that included intensive therapy, insulin use, proteinuria, and autonomic neuropathy. Consistent with prior reports in glucose-lowering studies, severe hypoglycemia occurred at a threefold significantly greater rate in those assigned to intensive glucose lowering. Second, severe hypoglycemia was associated with an increased risk of cardiovascular events, cardiovascular mortality, and all-cause mortality in both the standard and the intensive treatment groups. Of importance, however, severe hypoglycemia was associated with an even greater risk of all-cause mortality in the standard compared with the intensive treatment group. Third, the association between severe hypoglycemia and serious cardiovascular events was greater in individuals with an elevated risk for CVD at baseline.”

“Mean participant characteristics were as follows: age, 60.4 years; duration of diabetes, 11.5 years; BMI, 31.3 kg/m2; and HbA1c, 9.4%. Seventy-two percent had hypertension, 40% had a previous cardiovascular event, 62% had a microvascular complication, and 52% had baseline insulin use. The standard and intensive treatment groups included 899 and 892 participants, respectively. […] During the study, the standard treatment group averaged 3.7 severe hypoglycemic events per 100 patient-years versus 10.3 events per 100 patient-years in the intensive treatment group (P < 0.001). Overall, the combined rate of severe hypoglycemia during follow-up in the VADT from both study arms was 7.0 per 100 patient-years. […] Severe hypoglycemia within the prior 3 months was associated with an increased risk for composite cardiovascular outcome (HR 1.9 [95% CI 1.1, 3.5]; P = 0.03), cardiovascular mortality (3.7 [1.3, 10.4]; P = 0.01), and all-cause mortality (2.4 [1.1, 5.1]; P = 0.02) […]. More distant hypoglycemia (4–6 months prior) had no independently associated increased risk with adverse events or death. The association of severe hypoglycemia with cardiovascular events or cardiovascular mortality were not significantly different between the intensive and standard treatment groups […]. In contrast, the association of severe hypoglycemia with all-cause mortality was significantly greater in the standard versus the intensive treatment group (6.7 [2.7, 16.6] vs. 0.92 [0.2, 3.8], respectively; P = 0.019 for interaction). Because of the relative paucity of repeated severe hypoglycemic events in either study group, there was insufficient power to determine whether more than one episode of severe hypoglycemia increased the risk of subsequent outcomes.”

“Although recent severe hypoglycemia increased the risk of major cardiovascular events for those with a 10-year cardiovascular risk score of 35% (HR 2.88 [95% CI 1.57, 5.29]; absolute risk increase per 10 episodes = 0.252; number needed to harm = 4), hypoglycemia was not significantly associated with increased major cardiovascular events for those with a risk score of ≤7.5%. The absolute associated risk of major adverse cardiovascular events, cardiovascular mortality, and all-cause mortality increased with higher CVD risk for all three outcomes […]. We were not able to identify, however, any group of patients in either treatment arm in which severe hypoglycemia did not increase the risk of CVD events and mortality at least to some degree.”

“Although the explanation for the relatively greater risk of serious adverse events after severe hypoglycemia in the standard treatment group is unknown, we agree with previous reports that milder episodes of hypoglycemia, which are more frequent in the intensive treatment group, may quantitatively blunt the release of neuroendocrine and autonomic nervous system responses and their resultant metabolic and cardiovascular responses to hypoglycemia, thereby lessening the impact of subsequent severe hypoglycemic episodes (18,19). Episodes of prior hypoglycemia have rapid and significant effects on reducing (i.e., blunting) subsequent counterregulatory responses to a falling plasma glucose level (20,21). Thus, if one of the homeostatic counterregulatory responses (e.g., epinephrine) also can initiate unwanted intravascular atherothrombotic consequences, it may follow that severe hypoglycemia in a more intensively treated and metabolically well-controlled individual would provoke a reduced counterregulatory response. Although hypoglycemia frequency may be increased in these individuals, this may also lower unwanted and deleterious effects on the vasculature from counterregulatory responses. On the other hand, an isolated severe hypoglycemic event in a less well-controlled individual could provoke a relatively greater counterregulatory response with a proportionally attendant elevated risk for adverse vascular effects (22). In support of this, we previously reported in a subset of VADT participants that despite more frequent serious hypoglycemia in the intensive therapy group, progression of coronary artery calcium scores after severe hypoglycemia only occurred in the standard treatment group (23).”

“In the current study, we demonstrate that the association of severe hypoglycemia with subsequent serious adverse cardiovascular events and death occurred within the preceding 3 months but not beyond. The temporal relationship and proximity of severe hypoglycemia to a subsequent serious cardiovascular event and/or death has been investigated in a number of recent clinical trials in T2DM (25,13,14). All these trials consistently reported an association between severe hypoglycemic and subsequent serious adverse events. However, the proximity of severe hypoglycemic events to subsequent adverse events and death varies. In ADVANCE, a severe hypoglycemic episode increased the risk of major cardiovascular events for both the next 3 months and the following 6 months. In A Trial Comparing Cardiovascular Safety of Insulin Degludec Versus Insulin Glargine in Subjects With Type 2 Diabetes at High Risk of Cardiovascular Events (DEVOTE) and the Liraglutide Effect and Action in Diabetes: Evaluation of Cardiovascular Outcome Results (LEADER) trial, there was an increased risk of either serious cardiovascular events or all-cause mortality starting 15 days and extending (albeit with decreasing risk) up to 1 year after severe hypoglycemia (13,14).”

June 15, 2019 Posted by | Cardiology, Diabetes, Epidemiology, Genetics, Nephrology, Neurology, Ophthalmology, Studies | Leave a comment

A few diabetes papers of interest

i. Glycemic Control and Risk of Infections Among People With Type 1 or Type 2 Diabetes in a Large Primary Care Cohort Study. From the paper:

“Infections are widely considered to be a source of significant health care costs and to reduce quality of life among people with diabetes mellitus (DM) (1). Nevertheless, relatively few, large, well-designed, epidemiological studies have explored relationships between poorer control of DM and infections; previous studies have important limitations (1). Most randomized controlled trials (RCTs) of DM control have not investigated the effect of improved glycemic control on infections and are unlikely to do so at present because of the high cost and lack of good-quality supporting observational evidence. […] A recent review of higher-quality population-based epidemiological studies found clinically important (∼1.5–3.5 times higher) infection risks associated with poorer DM control in some studies (usually defined as a glycated hemoglobin [HbA1c] level >7–8% [53–64 mmol/mol]) (1). However, the studies were inconsistent, generating uncertainty about the evidence.

A key concern with previous work is that the measurement of HbA1c usually was made at or near to the time of the infection, so any association could be explained by reverse causality. Any infectious disease episode can itself have an adverse effect on glycemic control, a process known as stress hyperglycemia (4); hence, blood glucose or HbA1c measurements near the time of an infection may be elevated, rendering determination of the chronology and relationship between the two difficult. Several studies with serial HbA1c measurements have shown that the stress hyperglycemia response can be substantial (46). Another important issue is that studies of incident DM often use measurements of HbA1c obtained during initial presentation, and these typically do not represent subsequent levels after initiation of treatment; use of such measurements may obscure associations between usual HbA1c level and infection risk. Other limitations of previous work include a lack of consideration of type of DM (especially T1DM) and fewer older people with DM. The current study uses a large English primary care database with repeated HbA1c measurements wherein we can classify individuals more precisely in terms of their baseline glycemic control as well as ensure that these HbA1c measurements were made before the infection episode.”

“With the use of English primary care data, average glycated hemoglobin (HbA1c) during 2008–2009 was estimated for 85,312 patients with DM ages 40–89 years. Infection rates during 2010–2015 compiled from primary care, linked hospital, and mortality records were estimated across 18 infection categories and further summarized as any requiring a prescription or hospitalization or as cause of death. Poisson regression was used to estimate adjusted incidence rate ratios (IRRs) by HbA1c categories across all DM, and type 1 and type 2 DM separately. IRRs also were compared with 153,341 age-sex-practice–matched controls without DM. Attributable fractions (AF%) among patients with DM were estimated for an optimal control scenario (HbA1c 6–7% [42–53 mmol/mol]).”

“Crude infection rates during 2010–2015 estimated across 18 different categories confirmed consistently higher rates among patients with DM […]. Long-term infection risk rose with increasing HbA1c for most outcomes. Compared with patients without DM, those with DM and optimal control (HbA1c 6–7% [42–53 mmol/mol], IRR 1.41 [95% CI 1.36–1.47]) and poor control (≥11% [97 mmol/mol], 4.70 [4.24–5.21]) had elevated hospitalization risks for infection. In patients with type 1 DM and poor control, this risk was even greater (IRR 8.47 [5.86–12.24]). Comparisons within patients with DM confirmed the risk of hospitalization with poor control (2.70 [2.43–3.00]) after adjustment for duration and other confounders. AF% of poor control were high for serious infections, particularly bone and joint (46%), endocarditis (26%), tuberculosis (24%), sepsis (21%), infection-related hospitalization (17%), and mortality (16%). […] even patients with DM with good control were at an increased risk compared with matched controls without DM. Thus, compared with patients without DM, patients with DM and good control (mean HbA1c 6–7%, IRR 1.41 [95% CI 1.36–1.47]) and those with poor control (≥11%, 4.70 [4.24–5.21]) had elevated hospitalization risks for infection. These risks were higher among patients with T1DM. For example, patients with T1DM with a mean HbA1c ≥11%, had more than eight times the risk of hospitalization than their matched controls without DM (IRR 8.47 [5.86–12.24]), whereas for T2DM, this was four times higher (4.31 [3.88–4.80]). […] Patients with T1DM […] had higher rates of hospitalization (1.12 [1.01–1.24]) and death as a result of infection (1.42 [1.03–1.96]) than patients with T2DM, even after accounting for duration of DM.”

“In terms of the overall population effect, almost one-half of bone and joint infections among patients with DM were attributed to poor control. […] The most novel and concerning finding is the substantial proportion of other serious infections statistically attributable to poor glycemic control, particularly endocarditis, tuberculosis, and sepsis. Between 20 and 30% of these infections in the English DM population could be attributed to poor control. […] [W]e estimated AF% for the three summary groupings […] plus individual infection types […] across HbA1c categories for patients with DM compared with the optimal control scenario of 6–7%. The largest AF% estimate was for bone and joint infections, with 46.0% of hospitalizations being attributed to HbA1c values outside of the range 6–7%. Other large AF% estimates were observed for endocarditis (26.2%) and tuberculosis (23.7%), but CIs were wide. Sepsis (20.8%), pneumonia (15.3%), skin infections (cellulitis 14.0%, other 12.1%), and candidiasis (16.5%) all produced AF% estimates of ≥10%. Overall, 15.7% of infection-related deaths, 16.5% of infection-related hospitalizations, and 6.8% of infections requiring a prescription were attributed to values of HbA1c outside the 6–7% range.”

“Prevalence of diagnosed T2DM has tripled in the U.K. over the past 20 years (17). Although some improvements in glycemic control also have been observed over this period, our analyses show that substantial numbers of patients still have very poor glycemic control (e.g., 16% of patients with T2DM and 41% of patients with T1DM had a mean HbA1c >9%). […] 14% of patients with DM in the current study were hospitalized for infection during follow-up […] The U.K. has a relatively low prevalence of DM and good control on the basis of international comparisons (18); therefore, in many low- and middle-income countries, the burden of infections attributable to poor glycemic control could be substantially higher (19).”

“A variety of mechanisms may link DM and hyperglycemia with infection response (1,2022). Diabetes progression itself is associated with immune dysfunction; autoimmunity in T1DM and low-grade chronic inflammation in T2DM (1). Hyperglycemia may also have adverse effects on several types of immune cells (19,23); alter cytokine and chemokine gene expression (24), and inhibit effects of complement (25). Other important mechanisms may include peripheral diabetic neuropathy because this results in a loss of sensation and reduced awareness of minor injuries (13). Alongside ischemia, often as a result of related peripheral arterial disease, neuropathy can result in impaired barrier defenses, skin ulcers, and lesions with poor wound healing and an increased risk of secondary infections (19). Although numerous mechanisms exist, nearly all involve poor glycemic control. Thus, that improved control would reduce infections seems likely […] Overall, the current analyses demonstrate a strong and likely causal association between hyperglycemia and infection risk for both T1DM and T2DM. DM duration and other markers of severity cannot explain the increased risk, nor can longer duration explain the increased risk for T1DM compared with T2DM. This remains the case in older people in whom infections are common and often severe and more uncertainty exists about the vascular benefits of improving DM control. Substantial proportions of serious infections can be attributed to poor control, even though DM is managed well in the U.K. by international standards. Interventions to reduce infection risk largely have been ignored by the DM community and should be a high priority for future research.”

ii. Poor Metabolic Control in Children and Adolescents With Type 1 Diabetes and Psychiatric Comorbidity. Some observations from the paper:

“Type 1 diabetes in childhood has been found to be associated with an increased risk of psychiatric comorbidities (13), which might intensify the burden of disease and accelerate metabolic deterioration (46), subsequently increasing the risk of mortality and long-term complications such as retinopathy, nephropathy, and neuropathy (79).

Metabolic dysregulation is closely linked to age and diabetes duration, showing a peak in adolescence and early adulthood (10,11). Early adolescence is also characterized as a time of psychological vulnerability (12), in which the incidence of major psychiatric disorders increases (13). A diagnosis of type 1 diabetes in early adolescence seems to increase psychological distress (1,2), and three large population-based studies have shown higher rates of psychiatric disorders in children and adolescents with type 1 diabetes compared with the general population (13). In particular, increased risk was seen for depression, anxiety, and eating disorders, where the pathogenesis is considered to involve reactive mechanisms and imbalances in the diathesis-stress system (13,14).”

“Despite clinical and research evidence that a child with type 1 diabetes often receives more than one psychiatric diagnosis (1,3), most studies evaluate one disorder at a time (46,1620). Motivated by findings that Danish children and adolescents with type 1 diabetes have a higher risk of developing a psychiatric disorder compared with the background population (2), we performed two studies based on the NPR and the Danish Registry of Childhood and Adolescent Diabetes (DanDiabKids). […] The NPR contains psychiatric and somatic diagnoses from all inpatient admissions to Danish public hospitals since 1977. […] The register has used the ICD-10 since 1994 (22,23). Data on registration of psychiatric and type 1 diabetes diagnoses were collected from the NPR, covering 1996 to April 2015. DanDiabKids collects information on all children and adolescents diagnosed with type 1 diabetes before the age of 15 years and monitors them until they are transferred to adult clinics at ∼18 years of age. All public hospital pediatric units must supply annual data on all patients with diabetes to DanDiabKids. […] DanDiabKids contains annual data on all registered patients since 1996, including information on quality indicators, demographic variables, associated conditions, diabetes classification, diabetes family history, growth, self-management, and treatment variables. DanDiabKids now covers 99% of all Danish children and adolescents diagnosed with type 1 diabetes before the age of 15 years. […] Our study population was generated by merging data from DanDiabKids and the NPR. The inclusion criteria were registration with type 1 diabetes in DanDiabKids, age at onset <15 years, year of onset 1995–2014, and year of birth after 1980.”

“After merging DanDiabKids with the NPR, 4,725 children and adolescents with type 1 diabetes were identified […]. Characteristics for the included subjects were as follows: mean age at onset of diabetes was 8.98 years (SD 3.81), birth year ranged from 1980 to 2013, mean age at last visit was 14.6 years (3.7), 2,462 (52.1%) were boys, mean duration of diabetes at last visit was 5.65 years (3.7), 4,434 (93.8%) were of Danish origin, 254 (5.4%) were immigrants or offspring of immigrants, and 36 (0.8%) had unknown ethnicity. […] The observed number of SH [severe hypoglycemia, US] and DKA events per 100 person-years was respectively 10.7 (SH) and 3.2 (DKA) in patients with neurodevelopmental/constitutional psychiatric disorder, 12.1 (SH) and 3.7 (DKA) in patients with potentially reactive psychiatric disorder, 12.3 (SH) and 6.4 (DKA) in patients with both types of psychiatric disorders, and 8.1 (SH) and 1.8 (DKA) in patients without psychiatric disorder. […] Among the 4,725 children and adolescents included in the study, 1,035 were diagnosed with at least one psychiatric disorder at some point. Of these, a total of 175 received their first psychiatric diagnosis before the onset of type 1 diabetes, 575 during pediatric care, and 285 were diagnosed after referral to adult care. […] Anxiety disorders were the most common (n = 492), followed by “behavioral and emotional disorders” (n = 310), mood disorders (n = 205), psychoactive substance misuse disorders (n = 190), and disorders of inattention and hyperactivity (ADHD/attention-deficit disorder [ADD]) (n = 172). Of the 1,035 patients, 46% were diagnosed with two or more psychiatric disorders and 22.8% were diagnosed with three or more psychiatric disorders.”

“Shortly after type 1 diabetes diagnosis, a higher estimated risk of psychiatric disorders was evident among patients who were 10–15 years old at onset of type 1 diabetes. However, after 15–20 years with diabetes, the differences among the groups leveled out at a risk of ∼30% […] Children with high mean HbA1c levels (>8.5% [>70 mmol/mol]) during the first 2 years showed the highest estimated risk of developing a psychiatric disorder, although these differences also appear to level out after 15–20 years with type 1 diabetes. […] The mean HbA1c level was higher in children with a psychiatric disorder (0.22% [95% CI 0.15; 0.29]; 2.45 mmol/mol [1.67; 3.22]) compared with children with no psychiatric disorder (P < 0.001) […] High HbA1c levels in the early period after type 1 diabetes onset seem to be a possible indicator for subsequent psychiatric disorders, and having a psychiatric disorder was associated with higher HbA1c levels, especially in patients with disorders of putative reactive pathogenesis. Given that the Kaplan-Meier plots showed that the estimated risk of being diagnosed with a psychiatric disorder within a period of 15–20 years of type 1 diabetes onset was close to 30% in most groups, our finding highlights an important clinical problem.”

“The estimated risk of developing a psychiatric disorder during the 15–20 years after type 1 diabetes diagnosis is high. The most vulnerable period appeared to be adolescence. Patients with poorly regulated diabetes shortly after onset had a higher estimated risk of developing psychiatric comorbidities. Young patients diagnosed with a psychiatric disorder had more episodes of DKA, and those diagnosed within the reactive spectrum had higher HbA1c levels. Children and adolescents with type 1 diabetes, and in particular those who fail to reach treatment goals, should be systematically evaluated regarding psychological vulnerabilities.”

iii. Development of Microvascular Complications and Effect of Concurrent Risk Factors in Type 1 Diabetes: A Multistate Model From an Observational Clinical Cohort Study.

“The prevalence of type 1 diabetes has increased over the past decades (1,2). Increased life expectancy means that people live longer with diabetes (35); thus, potentially more years are lived with both macrovascular and microvascular complications (6,7). Type 1 diabetes is a complex disease, which develops in various complication states, and co-occurrence of multiple microvascular complications frequently is seen (8). So far, most studies are of a single complication, and the association between the worsening of one complication and the incidence of another is well described, although independently of other complications (9,10). At the same time, a sizeable group of individuals seems to be protected from microvascular complications (1114), and some live several decades with type 1 diabetes without developing complications. Advanced statistical models, such as multistate models, offer an opportunity to explore the transition through various disease states and to quantify progression rates while considering the concurrent complication burden (15,16), that is, the complication burden at a given time point in the observation window.

Strong evidence indicates that some risk factors play a role in all types of microvascular complications. For example, the effects of the duration of diabetes and poor glycemic control are well documented (1720). For other risk factors, such as hypertension, an association has been established mainly for retinopathy and diabetic kidney disease (21,22). Adverse cholesterol levels and previous cardiovascular disease (CVD) are indisputably associated with a higher risk of macrovascular complications (23) and may play a role in the development of microvascular complications (24). […] The complex interplay between microvascular complications and risk factors has been explored only to a limited extent. In this study, we developed a multistate model of microvascular complications to describe in detail complication development in type 1 diabetes. We describe the development of sequences of diabetes-related microvascular complications at various states and examine the associations between selected risk factors, both alone and combined with existing complication burden, and incidence of (further) microvascular complications.”

“In total, 5,031 individuals with type 1 diabetes were registered at the SDCC during the study period. We excluded 1,203 because of missing data for diabetic kidney disease, retinopathy, and/or neuropathy, which left 3,828 eligible individuals to be included in the study. Of these, 242 were first seen in the final state with three complications, which left 3,586 available for analysis, corresponding to 22,946 person-years (PY) […] The median follow-up time was 7.8 years (25th–75th percentile 3.3–10.7 years). HbA1c level at the end of follow-up was lower than at entry, whereas the levels of blood pressure, lipids, and BMI were unchanged. An increase in the use of all cardioprotective medications was observed.”

“We identified 523 individuals who developed diabetic kidney disease during the study. Of these, 84 events occurred in individuals with no complications (IR 12.9 per 1,000 PY), 221 in individuals with retinopathy (25.7 per 1,000 PY), 27 in individuals with neuropathy (36.6 per 1,000 PY), and 191 in individuals with both neuropathy and retinopathy (61.8 per 1,000 PY). […] In the adjusted model, individuals with both retinopathy and neuropathy had a threefold higher risk of diabetic kidney disease than individuals without complications. […] A total of 482 individuals developed neuropathy during follow-up. Of these, 75 incidents occurred in individuals with no complications (IR 11.5 per 1,000 PY), 14 in individuals with diabetic kidney disease (20.6 per 1,000 PY), 234 in individuals with retinopathy (27.2 per 1,000 PY), and 159 in individuals with both retinopathy and diabetic kidney disease (50.2 per 1,000 PY). Individuals with both retinopathy and diabetic kidney disease had a 70% higher risk of developing neuropathy than individuals without complications […] In total, we recorded 649 individuals with incident retinopathy from any previous complication state. Of these, 459 incidents occurred in individuals with no complications (IR 70.7 per 1,000 PY), 74 in individuals with diabetic kidney disease (109.1 per 1,000 PY), 71 in individuals with neuropathy (96.6 per 1,000 PY), and 45 in individuals with both neuropathy and diabetic kidney disease (224.7 per 1,000 PY). Individuals with both diabetic kidney disease and neuropathy had a twofold higher IRR of developing retinopathy than individuals without complications”.

“Baseline and concurrent values of HbA1c, systolic blood pressure, eGFR, and baseline CVD status were all strongly associated with a higher risk of developing diabetic kidney disease. […] The analysis that included complication state revealed that individuals without any other complications than CVD had an almost three times higher risk of diabetic kidney disease than individuals without either CVD or microvascular complications. […] Duration of diabetes, baseline and concurrent value of HbA1c, systolic blood pressure, and baseline LDL cholesterol values were all factors associated with a higher risk of developing retinopathy. None of the effects of the modifiable risk factors on retinopathy were modified by complication burden. […] men with diabetic kidney disease had a higher risk of developing retinopathy than women with diabetic kidney disease. […] All investigated risk factors, except LDL cholesterol, were associated with incidence of neuropathy at both baseline and concurrent levels.”

“[W]e conducted a sensitivity analysis with retinopathy defined as severe nonproliferative or proliferative retinopathy. The prevalence and incidence of retinopathy were much lower, but all associations were similar to the main analysis […]. We found no effect modification by lipid-lowering or antihypertensive treatment. […] We found a stepwise higher risk of any microvascular complication in individuals with higher concurrent complication burden. Baseline and concurrent HbA1c levels, systolic blood pressure, and duration of diabetes were associated with the development of all three microvascular complications. For most risk factors, we did not find evidence that concurrent complication burden modified the association with complication development. […] Concurrent HbA1c level was a strong risk factor for all microvascular complications, even when we adjusted for age, duration, and other traditional risk factors. The overall effects were of similar magnitude to the effect of baseline levels of HbA1c and to other reports (11,29).”

“The presented results are interpreted in the frame of a multistate model design, and the use of clinical data makes the results highly relevant in similar health care settings. However, because of the observational study design, we cannot draw conclusions about causality. The positive associations among complications might reflect that diabetic kidney disease takes the longest time to develop, whereas retinopathy and neuropathy develop faster. Associations of two disease complications to a third might not be causal. However, that the risk of a third complication, even after adjustment for multiple confounders, is higher regardless of the previous combination of complications indicates that an association cannot be explained by these risk factors alone. In addition, concurrent risk factor levels may be subject to reverse causality. The current results should be seen as a benchmark for others who aim to explore the occurrence of microvascular complications as a function of the concurrent total complication burden in individuals with type 1 diabetes. […] The findings demonstrate that high concurrent complication burden elevates the risk of all three investigated microvascular complications: diabetic kidney disease, retinopathy, and neuropathy. This means that if an individual develops a complication, the clinician should be aware of the increased risk of developing more complications. […] For most risk factors, including HbA1c, we found no evidence that the effect on the development of microvascular complications was modified by the burden of concurrent complications.”

iv. Long-term Glycemic Control and Dementia Risk in Type 1 Diabetes.

“[P]rior work has established type 1 diabetes as a risk factor for dementia (15). However, the relationship between glycemic control and subsequent risk of dementia in those with type 1 diabetes remains unclear. Hemoglobin A1c (HbA1c) is an established measure that integrates glucose control over the prior 2–3 months and is widely used to guide clinical management of type 1 diabetes (16,17). Cumulative glycemic exposure, as measured by multiple HbA1c measures over time, has previously been used to evaluate glycemic trajectories and their association with a number of diabetes complications (18,19). Electronic health records capture HbA1c values collected over time allowing for a more thorough long-term characterization of glycemic exposure than is reflected by a single HbA1c measure. In this study, we leverage data [from northern California, US] collected over a span of 19 years to examine the association of cumulative glycemic exposure, as measured by repeated HbA1c values, with incident dementia among older adults with type 1 diabetes. We also examine the potential for a threshold of glycemic exposure above or below which risk of dementia increases.”

“The final analytic cohort consisted of 3,433 individuals (mean age at cohort entry = 56.1 years old; 47.1% female) […]. On average, individuals who developed dementia during follow-up were older at cohort entry (64.4 vs. 55.7 years) and were more likely to have a history of stroke (7.7% compared with 3.5%) at baseline. The mean follow-up time was 6.3 years (median 4.8 years [interquartile range (IQR) 1.7, 9.9]), and the mean number of HbA1c measurements was 13.5 (median 9.0 [IQR 3.0, 20.00]). By the end of follow-up on 30 September 2015, 155 members (4.5%) were diagnosed with dementia, 860 (25.1%) had a lapse of at least 90 days in membership coverage, 519 (15.1%) died without a dementia diagnosis, and 1,899 (55.3%) were still alive without dementia diagnosis. Among the 155 members who developed dementia over follow-up, the mean age at dementia diagnosis was 64.6 years (median 63.6 years [IQR 56.1, 72.3]).”

“In Cox proportional hazards models, dementia risk was higher in those with increased exposure to HbA1c 8–8.9% (64–74 mmol/mol) and ≥9% (≥75 mmol/mol) and lower in those with HbA1c 6–6.9% (42–52 mmol/mol) and 7–7.9% (53–63 mmol/mol). In fully adjusted models, compared with those with minimal exposure (<10% of HbA1c measurements) to HbA1c 8–8.9% and ≥9%, those with prolonged exposure (≥75% of measurements) were 2.51 and 2.13 times more likely to develop dementia, respectively (HbA1c 8–8.9% fully adjusted hazard ratio [aHR] 2.51 [95% CI 1.23, 5.11] and HbA1c ≥9% aHR 2.13 [95% CI 1.13, 4.01]) […]. In contrast, prolonged exposure to HbA1c 6–6.9 and 7–7.9% was associated with a 58% lower and 61% lower risk of dementia, respectively (HbA1c 6–6.9% aHR 0.42 [95% CI 0.21, 0.83] and HbA1c 7–7.9% aHR 0.39 [95% CI 0.18, 0.83]). […] Results were similar in Cox models examining cumulative glycemic exposure based on whether a majority (>50%) of an individual’s available HbA1c measurements fell into the following categories of HbA1c: <6, 6–6.9, 7–7.9, 8–8.9, and ≥9% […]. Majority exposure to HbA1c 8–8.9 and ≥9% was associated with an increased risk of dementia (HbA1c 8–8.9% aHR 1.65 [95% CI 1.06, 2.57] and HbA1c ≥9% aHR 1.79 [95% CI 1.11, 2.90]), while majority exposure to HbA1c 6–6.9 and 7–7.9% was associated with a reduced risk of dementia (HbA1c 6–6.9% aHR 0.55 [95% CI 0.34, 0.88] and HbA1c 7–7.9% aHR 0.55 [95% CI 0.37, 0.82]). Majority exposure to HbA1c <6% (<42 mmol/mol) was associated with increased dementia risk in age-adjusted models (HR 2.06 [95% CI 1.11, 3.82]), though findings did not remain significant in fully adjusted models (aHR 1.45 [95% CI 0.71, 2.92]). Findings were similar in sensitivity analyses among the subset of members who were ≥65 years of age at baseline (n = 1,082 [32% of the sample]), though the increased risk associated with majority time at HbA1c ≥9% was no longer statistically significant”.

“In this large sample of older adults with type 1 diabetes, we found that cumulative exposure to higher levels of HbA1c (8–8.9 and ≥9%) was associated with an increased risk of dementia, while cumulative exposure to well-controlled HbA1c (6–6.9 and 7–7.9%) was associated with a decreased risk of dementia. In fully adjusted models, compared with those with minimal exposure to HbA1c 8–8.9% and HbA1c ≥9%, those with prolonged exposure were more than twice as likely to develop dementia over the course of follow-up […]. By contrast, dementia risk was ∼60% lower among those with prolonged exposure to well-controlled HbA1c (6–6.9 and 7–7.9%) compared with those with minimal time at well-controlled levels of HbA1c.”

“Our results complement and extend previous studies that have reported an association between chronic hyperglycemia and decreased cognitive function in children and adolescents with type 1 diabetes (25,26), as well as studies reporting an association between poor glycemic control and decreased cognitive functioning in middle-aged adults with type 1 diabetes and older adults with type 2 diabetes (711). Our findings are also consistent with previous studies that found an increased dementia risk associated with poorer glycemic control among adults with type 2 diabetes and adults without diabetes (1113). Whether these findings applied to dementia risk among older adults with type 1 diabetes was previously unknown.”

“In our study of 3,433 older adults with type 1 diabetes, 155 (4.5%) individuals developed dementia over an average of 6.3 years of follow-up. Among those who developed dementia, the average age at dementia diagnosis was 64.6 years. A large-scale study using administrative health data from 1998 to 2011 in England reported a similar incidence of dementia among a subset of adults aged ≥50 years with type 1 diabetes (3.99% developed dementia), though the average length of follow-up was not reported for this specific age-group (15). Prior studies have also found type 1 diabetes to be a risk factor for dementia (15) and have reported the average age at onset of dementia to be 2–5 years earlier in those with diabetes compared with those without diabetes (27,28). Taken together, these results provide further evidence that older adults with type 1 diabetes are at increased risk of developing dementia and may have increased risk at younger ages than the general population. Our results, however, suggest that effective glycemic control could be an important tool for reducing risk of dementia among older adults with type 1 diabetes.”

“Pathophysiological mechanisms by which glycemic control may affect dementia risk are still poorly understood but are hypothesized to result from structural brain abnormalities stemming from chronic exposure to hyperglycemia and/or recurrent severe hypoglycemia. Studies in adults and youth with type 1 diabetes have reported an association between chronic hyperglycemia (defined using lifetime HbA1c history and using retinopathy as an indicator of chronic exposure) and gray matter density loss (3537). Studies examining the association between severe hypoglycemic events and changes in brain structure have been less consistent, with some reporting increased gray matter density loss and a higher prevalence of cortical atrophy in those with a history of frequent exposure to severe hypoglycemia (36,38), while another study reported no association (37). In the ACCORD MIND (Action to Control Cardiovascular Risk in Diabetes Memory in Diabetes) trial, compared with standard glycemic control, intensive glycemic control was associated with greater total brain volume, suggesting that intensive glycemic control may reduce brain atrophy related to diabetes (39). […] Understanding why glycemic patterns are associated with dementia is a much-needed area for future study, particularly with regard of the potential role of intercurrent micro- and macrovascular complications.”

v. A Comparison of the 2017 American College of Cardiology/American Heart Association Blood Pressure Guideline and the 2017 American Diabetes Association Diabetes and Hypertension Position Statement for U.S. Adults With Diabetes.

“Hypertension is one of the most common comorbidities among adults with diabetes. Prior studies have estimated the prevalence of hypertension to be twice as high among adults with diabetes compared with age-matched control subjects without diabetes (1,2). Among adults with diabetes, the presence of hypertension has been associated with a two times higher risk for cardiovascular disease (CVD) events and mortality (3,4).

The 2017 American College of Cardiology (ACC)/American Heart Association (AHA) Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults provides a comprehensive set of recommendations for the diagnosis and treatment of hypertension among adults, including those with diabetes (5). This guideline defines hypertension in adults, including those with diabetes, as an average systolic blood pressure (SBP) ≥130 mmHg or diastolic blood pressure (DBP) ≥80 mmHg […]. According to this guideline, pharmacological antihypertensive treatment should be initiated in adults with diabetes if they have an average SBP ≥130 mmHg or DBP ≥80 mmHg, and the treatment goal is SBP <130 mmHg and DBP <80 mmHg (5).

The American Diabetes Association (ADA) published a position statement on diabetes and hypertension in 2017 that recommends blood pressure (BP) levels different from the ACC/AHA guideline for defining hypertension and for initiating pharmacological antihypertensive treatment (for both, SBP ≥140 mmHg or DBP ≥90 mmHg) (6). The ADA position statement recommends that BP goals should be individualized based on patient priorities and clinician judgment. Treatment goals for those taking antihypertensive medication are SBP <140 mmHg and DBP <90 mmHg, with SBP <130 mmHg and DBP <80 mmHg to be considered for those with high CVD risk as long as these levels can be achieved without undo treatment burden.

The purpose of the current study was to estimate the impact of differences in the definition of hypertension and recommendations for pharmacological antihypertensive treatment initiation and intensification of therapy in U.S. adults with diabetes according to the ACC/AHA guideline and the ADA diabetes and hypertension position statement (5,6). To accomplish these goals, we analyzed data from the U.S. National Health and Nutrition Examination Survey (NHANES).”

“According to data from NHANES 2011–2016, 56.6% (95% CI 53.3, 59.9) of U.S. adults with diabetes were taking antihypertensive medication. Of U.S. adults with diabetes, 57.4% (53.1, 61.6) of those not taking and 80.2% (76.6, 83.4) of those taking antihypertensive medication had high CVD risk. Among U.S. adults with diabetes, those with high CVD risk (history of CVD or 10-year ASCVD risk ≥10%) were on average 15–20 years older and the prevalence of smoking and chronic kidney disease was 10–20% higher when compared with their counterparts without high CVD risk […]. Among U.S. adults with diabetes without high CVD risk, the mean 10-year and 30-year predicted CVD risks were 3.8% (3.5, 4.2) and 25.0% (23.4, 26.6), respectively, for those not taking antihypertensive medication and 5.8% (5.3, 6.4) and 37.4% (34.5, 40.3), respectively, for those taking antihypertensive medication.

The prevalence of hypertension was 77.1% (95% CI 73.9, 80.0) according to the ACC/AHA guideline and 66.3% (63.4, 69.1) according to the ADA position statement […]. Overall, 10.8% (9.0, 12.8) of U.S. adults with diabetes had hypertension according to the ACC/AHA guideline but not the ADA position statement. Among U.S. adults with diabetes not taking antihypertensive medication, 52.8% (47.7, 57.8), 24.8% (20.6, 29.6) and 22.4% (19.2, 25.9) were recommended antihypertensive medication initiation by neither document, by the 2017 ACC/AHA guideline only, and by both documents, respectively […]. Among U.S. adults with diabetes taking antihypertensive medication, 45.3% (41.3, 49.4), 4.3% (2.8, 6.6), and 50.4% (46.5, 54.2) had an average BP that met the goal in both documents, was above the ACC/AHA goal but not the ADA goal, and was above the goals in both documents, respectively […] The overall agreement between the ACC/AHA guideline and the ADA position statement was 89.2% (87.2, 91.0) for the presence of hypertension, 75.2% (70.4, 79.4) for the recommendation to initiate antihypertensive medication, and 95.7% (93.4, 97.2) for having a BP above the recommended treatment goal. “

“Based on both the ACC/AHA guideline and ADA position statement, 17.8 (95% CI 16.2, 19.3) million U.S. adults with diabetes had hypertension […]. An additional 2.9 (2.3, 3.5) million U.S. adults had hypertension based on the ACC/AHA guideline only. Among U.S. adults with diabetes not taking antihypertensive medication, 2.6 (2.1, 3.1) million were recommended to initiate antihypertensive medication by both the ACC/AHA guideline and the ADA position statement with an additional 2.9 (2.3, 3.5) million recommended to initiate antihypertensive medication by the ACC/AHA guideline only […]. Among U.S. adults with diabetes taking antihypertensive medication, 7.6 (6.8, 8.5) million had a BP above the goal in both documents, with an additional 700,000 (400,000, 900,000) having a BP above the goal recommended in the ACC/AHA guideline only […]. Among U.S. adults with diabetes not taking antihypertensive medication, the mean 10-year CVD risk was 10.7% (95% CI 9.4, 12.0) for those not recommended treatment initiation by either the ACC/AHA guideline or the ADA position statement, 14.6% (11.5, 17.6) for those recommended treatment initiation by the ACC/AHA guideline but not the ADA position statement, and 23.2% (19.5, 27.0) among those recommended treatment initiation by the ACC/AHA guideline and the ADA position statement […]. The mean 30-year CVD risk exceeded 25% in each of these groups. Among U.S. adults with diabetes taking antihypertensive medication, the mean 10-year CVD risk was 10.6% (9.4, 12.0), 6.5% (CI 5.6, 7.3), and 33.8% (32.1, 35.5) among those with above-goal BP according to neither document, the ACC/AHA guideline only, and both documents, respectively […]. The 30-year CVD risk exceeded 40% in each group.”

“In conclusion, the current study demonstrates a high degree of concordance between the 2017 ACC/AHA BP guideline and the 2017 ADA position statement on diabetes and hypertension. Using either document, the majority of U.S. adults with diabetes have hypertension. A substantial proportion of U.S. adults with diabetes not taking antihypertensive medication are recommended to initiate treatment by both documents […] Among U.S. adults with diabetes not taking antihypertensive medication, 75.2% had an identical recommendation for initiation of antihypertensive drug therapy according to the ACC/AHA guideline and the ADA position statement. The majority of those who were recommended to initiate pharmacological antihypertensive therapy according to the ACC/AHA guideline but not the ADA position statement had high CVD risk. […] At the population level, the ACC/AHA guideline and ADA position statement have more similarities than differences. However, at the individual level, some patients with diabetes will have fundamental changes in their care depending on which advice is followed. The decision to initiate and intensify antihypertensive medication should always be individualized, based on discussions between patients and their clinicians. Both the ACC/AHA BP guideline and ADA position statement acknowledge the need to individualize treatment decisions to align with patients’ interests.”

vi. Treatment-induced neuropathy of diabetes: an acute, iatrogenic complication of diabetes.

“Treatment-induced neuropathy in diabetes (also referred to as insulin neuritis) is considered a rare iatrogenic small fibre neuropathy caused by an abrupt improvement in glycaemic control in the setting of chronic hyperglycaemia. The prevalence and risk factors of this disorder are not known. In a retrospective review of all individuals referred to a tertiary care diabetic neuropathy clinic over 5 years, we define the proportion of individuals that present with and the risk factors for development of treatment-induced neuropathy in diabetes. Nine hundred and fifty-four individuals were evaluated for a possible diabetic neuropathy. Treatment-induced neuropathy in diabetes was defined as the acute onset of neuropathic pain and/or autonomic dysfunction within 8 weeks of a large improvement in glycaemic control—specified as a decrease in glycosylated haemoglobin A1C (HbA1c) of ≥2% points over 3 months. Detailed structured neurologic examinations, glucose control logs, pain scores, autonomic symptoms and other microvascular complications were measured every 3–6 months for the duration of follow-up. Of 954 patients evaluated for diabetic neuropathy, 104/954 subjects (10.9%) met criteria for treatment-induced neuropathy in diabetes with an acute increase in neuropathic or autonomic symptoms or signs coinciding with a substantial decrease in HbA1c. Individuals with a decrease in HbA1c had a much greater risk of developing a painful or autonomic neuropathy than those individuals with no change in HbA1c (P < 0.001), but also had a higher risk of developing retinopathy (P < 0.001) and microalbuminuria (P < 0.001). There was a strong correlation between the magnitude of decrease in HbA1c, the severity of neuropathic pain (R = 0.84, P < 0.001), the degree of parasympathetic dysfunction (R = −0.52, P < 0.01) and impairment of sympathetic adrenergic function as measured by fall in blood pressure on tilt-table testing (R = −0.63, P < 0.001). With a decrease in HbA1c of 2–3% points over 3 months there was a 20% absolute risk of developing treatment-induced neuropathy in diabetes, with a decrease in HbA1c of >4% points over 3 months the absolute risk of developing treatment-induced neuropathy in diabetes exceeded 80%. Treatment-induced neuropathy of diabetes is an underestimated iatrogenic disorder associated with diffuse microvascular complications. Rapid glycaemic change in patients with uncontrolled diabetes increases the risk of this complication.”

“Typically, individuals with TIND reported the onset of severe burning pain (pain scores 4–10/10) within 2–6 weeks of the improvement in glucose control. Burning pain was present in all subjects with TIND. Paraesthesias were present in 93/104 subjects and shooting pain in 88/104 subjects. Hyperalgesia and allodynia were common in the distribution of the pain. […] Individuals with TIND all reported ongoing sleep disturbances typically described as difficulty with sleep initiation and sleep duration secondary to neuropathic pain. These individuals reported no record of sleep problems prior to the development of TIND. […] Erectile dysfunction was noted in 28/31 males with TIND, compared to 135/417 males without TIND (P < 0.001, X2). […] Seventy-three individuals completed autonomic testing within 2–5 months of the onset of neuropathic pain. […] The results for both groups, in all tests, were abnormal compared to age-related normative values. There were strong correlations between the magnitude of decrease in HbA1c over 3 months and worsening autonomic function. A greater change in HbA1c resulted in worsening parasympathetic function as determined by the expiratory to inspiratory ratio (R = −0.52, P < 0.01) and the Valsalva ratio (R = −0.55, P < 0.01). Greater sympathetic adrenergic dysfunction also correlated with a greater change in HbA1c over 3 months as determined by the fall in systolic blood pressure during tilt-table test (R = −0.63, P < 0.001), the fall in blood pressure during phase 2 of the Valsalva manoeuvre (R = 0.49, P < 0.001), and the diminished phase 4 blood pressure overshoot during the Valsalva manoeuvre (R = −0.59, P < 0.001). […] individuals with type 1 diabetes had greater autonomic dysfunction than those with type 2 diabetes across all tests. The slopes of the regression lines describing the correlation between the change in HbA1c and a particular autonomic test did not differ by the type of diabetes, or by the type of treatment used to control glucose.”

“Most patients with TIND had rapid progression of retinopathy that developed in conjunction with the onset of neuropathic pain […] Prior to development of TIND, 65/104 individuals had no retinopathy, 35/104 had non-proliferative retinopathy, whereas 4/104 had proliferative retinopathy. Twelve months after the development of TIND, 10/104 individuals had no retinopathy, 54/104 had non-proliferative retinopathy and 40/104 had proliferative retinopathy (P < 0.001, Fisher’s exact test). Prior to development of TIND, 18/104 had evidence of microalbuminuria, while 12 months after the development of TIND, 87/104 had evidence of microalbuminuria (P < 0.001, X2).”

“TIND is a small fibre and autonomic neuropathy that appears after rapid improvements in glucose control. In this manuscript, we demonstrate that: (i) there is an unexpectedly high proportion of individuals with TIND in a tertiary referral diabetic clinic; (ii) the risk of developing TIND is associated with the magnitude and rate of change in HbA1c; (iii) neuropathic pain and autonomic dysfunction severity correlate with the magnitude of change in HbA1c; (iv) patients with Type 1 diabetes and a history of eating disorders are at high risk for developing TIND; and (v) TIND can occur with use of insulin or oral hypoglycaemic agents. […] TIND differs from the most prevalent generalized neuropathy of diabetes, the distal sensory-motor polyneuropathy, in several respects. The neuropathic pain has an acute onset, appearing within 8 weeks of glycaemic change, in contrast with the more insidious onset in the distal sensory-motor polyneuropathy […]. The pain in TIND is more severe, and poorly responsive to interventions including opioids, whereas most patients with distal sensory-motor polyneuropathy respond to non-opioid interventions […]. Although the distribution of the pain is length-dependent in individuals with TIND, it is frequently far more extensive than in distal sensory-motor polyneuropathy and the associated allodynia and hyperalgesia are much more prevalent […]. Autonomic symptoms and signs are common, prominent and appear acutely, in contrast to the relatively lower prevalence, gradual onset and slow progression in distal sensory-motor polyneuropathy […]. Finally, both the pain and autonomic features may be reversible in some patients […].

Our data indicate that the severity of TIND is associated with the magnitude of the change of HbA1c, however, it is also clear that the rate of change is important (e.g. a 4% point fall in the HbA1c will have a greater impact if occurring over 3 months than over 6 months). The pathogenic mechanisms whereby this change in glucose results in nerve damage and/or dysfunction are not known. Proposed mechanisms include endoneurial ischaemia due to epineurial arterio-venous shunts […], apoptosis due to glucose deprivation […], microvascular neuronal damage due to recurrent hypoglycaemia […], and ectopic firing of regenerating axon sprouts, but these possibilities are unproven. […] Additional mechanistic studies are necessary to determine the underlying pathophysiology.”

April 28, 2019 Posted by | Cardiology, Diabetes, Epidemiology, Immunology, Medicine, Nephrology, Neurology, Ophthalmology, Psychiatry, Studies | Leave a comment

Oncology (II)

Here’s my first post in this series. Below some more quotes and links related to the book’s coverage.

Types of Pain
1. Nociceptive pain
a. Somatic pain: Cutaneous or musculoskeletal tissue (ie, bone, soft tissue metastases). Usually well-localized, increased w/use/movement.
b. Visceral pain: Compression, obstruction, infiltration, ischemia, stretching, or inflammation of solid & hollow viscera. Diffuse, nonfocal.
2. Neuropathic pain: Direct injury/dysfunction of peripheral or CNS tissues. Typically burning, radiating, may increase at rest or w/nerve stretching.
Pain emergencies: Pain crisis, spinal cord compression, fracture, bowel obstruction, severe mucositis, acute severe side effects of opioids (addiction crisis, delirium, respiratory depression), severe pain in imminently dying pt [patient, US]
Pain mgmt at the end of life is a moral obligation to alleviate pain & unnecessary suffering & is not euthanasia. (Vacco vs. Quill, U.S. Supreme Court, 1997)”

Nausea and Vomiting
Chemotherapy-induced N/V — 3 distinct types: Acute, delayed, & anticipatory. Acute begins 1–2 h after chemotherapy & peaks at 4–6 h, delayed begins at 24 h & peaks at 48–72 h, anticipatory is conditioned response to nausea a/w previous cycles of chemotherapy”

Constipation […] affects 50% of pts w/advanced CA; majority of pts being treated w/opioid analgesics, other contributors: malignant obstruction, ↓ PO/fluid intake, inactivity, anticholinergics, electrolyte derangement”

Fatigue
Prevalence/screening — occurs in up to 75% of all solid tumor pts & up to 99% of CA pts receiving multimodality Rx. Providers should screen for fatigue at initial visit, at dx [diagnosis, US] of advanced dz [disease] & w/each chemo visit; should assess for depression & insomnia w/new dx of fatigue (JCO 2008;23:3886) […] Several common 2° causes to eval & target include anemia (most common), thyroid or adrenal insufficiency, hypogonadism”

Delirium
*Definition — disturbances in level of consciousness, attention, cognition, and/or perception developing abruptly w/fluctuations over course of d *Clinical subtypes — hyperactive, hypoactive, & mixed […] *Maximize nonpharm intervention prior to pharmacology […] *Use of antipsychotics should be geared toward short-term use for acute sx [symptoms, US] *Benzodiazepines should only be initiated for delirium as an adjunct to antipsychotics in setting of agitation despite adequate antipsychotic dosing (JCO 2011;30:1206)”

Cancer Survivorship
Overview *W/improvement in dx & tx of CA, there are millions of CA survivors, & this number is increasing
*Pts experience the normal issues of aging, w/c are compounded by the long-term effects of CA & CA tx
*CA survivors are at ↑ risk of developing morbidity & illnesses at younger age than general population due to their CA tx […] ~312,570 male & ~396,080 female CA survivors <40 y of age (Cancer Treatment and Survivorship Facts and Figures 2016–2017, ACS) *Fertility is an important issue for survivors & there is considerable concern about the possibility of impairment (Human Reproduction Update 2009;15:587)”

“Pts undergoing cancer tx are at ↑ risk for infxn [infection, US] due to disease itself or its therapies. […] *Epidemiology: 10–50% of pts w/ solid tumors & >80% of pts with hematologic tumors *Source of infxn evident in only 20–30% of febrile episodes *If identified, common sites of infxn include blood, lungs, skin, & GI tract *Regardless of microbiologic diagnosis, Rx should be started within 2 h of fever onset which improves outcomes […] [Infections in the transplant host is the] Primary cause of death in 8% of auto-HCT & up to 20% of allo-HCT recipients” [here’s a relevant link, US].

Localized prostate cancer
*Epidemiology Incidence: ~180000, most common non-skin CA (2016: U.S. est.) (CA Cancer J Clin 2016:66:7) *Annual Mortality: ~26000, 2nd highest cause of cancer death in men (2016: U.S. est) […] Mortality benefit from screening asx [asymptomatic, US] men has not been definitively established, & individualized discussion of potential benefits & harms should occur before PSA testing is offered. […] Gleason grade reflects growth/differentiation pattern & ranges from 1–5, from most to least differentiated. […] Historical (pre-PSA) 15-y prostate CA mortality risk for conservatively managed (no surgery or RT) localized Gleason 6: 18–30%, Gleason 7: 42–70%, Gleason 8–10: 60–87% (JAMA 1998:280:975)”

Bladder cancer […] Most common malignancy of the urinary system, ~77000 Pts will be diagnosed in the US in 2016, ~16000 will die of their dz. […] Presenting sx: Painless hematuria (typically intermittent & gross), irritative voiding sx (frequency, urgency, dysuria), flank or suprapubic pain (symptomatic of locally advanced dz), constitutional sx (fatigue, wt loss, failure to thrive) usually symptomatic of met [metastatic, US] dz

Links:

WHO analgesia ladder. (But see also this – US).
Renal cell carcinoma (“~63000 new cases & ~1400 deaths in the USA in 2016 […] Median age dx 64, more prevalent in men”)
Germ cell tumour (“~8720 new cases of testicular CA in the US in 2016 […] GCT is the most common CA in men ages of 15 to 35 y/o”)
Non-small-cell lung carcinoma (“225K annual cases w/ 160K US deaths, #1 cause of cancer mortality; 70% stage III/IV *Cigarette smoking: 85% of all cases, ↑ w/ intensity & duration of smoking”)
Small-cell lung cancer. (“SCLC accounts for 13–15% of all lung CAs, seen almost exclusively in smokers, majority w/ extensive stage dz at dx (60–70%). Lambert–Eaton myasthenic syndrome (“Affects 3% of SCLC pts”).
Thymoma. Myasthenia gravis. Morvan’s syndrome. Masaoka-Koga Staging system.
Pleural mesothelioma (“Rare; ≅3000 new cases dx annually in US. Commonly develops in the 5th to 7th decade […] About 80% are a/w asbestos exposure. […] Develops decades after asbestos exposure, averaging 30–40 years […] Median survival: 10 mo. […] Screening has not been shown to ↓ mortality even in subjects w/ asbestos exposure”)
Hepatocellular Carcinoma (HCC). (“*6th most common CA worldwide (626,000/y) & 2nd leading cause of worldwide CA mortality (598,000/y) *>80% cases of HCC occur in sub-Saharan Africa, eastern & southeastern Asia, & parts of Oceania including Papua New Guinea *9th leading cause of CA mortality in US […] Viral hepatitis: HBV & HCV are the leading RFs for HCC & accounts for 75% cases worldwide […] While HCV is now the leading cause of HCC in the US, NASH is expected to become a risk factor of increasing importance in the next decade”). Milan criteria.
CholangiocarcinomaKlatskin tumor. Gallbladder cancer. Courvoisier’s sign.
Pancreatic cancer (Incidence: estimated ~53,070 new cases/y & ~42,780 D/y in US (NCI SEER); 4th most common cause of CA death in US men & women; estimated to be 2nd leading cause of CA-related mortality by 2020″). Trousseau sign of malignancy. Whipple procedure.

October 21, 2018 Posted by | Books, Cancer/oncology, Gastroenterology, Medicine, Nephrology, Neurology, Psychiatry | Leave a comment

A few diabetes papers of interest

i. Islet Long Noncoding RNAs: A Playbook for Discovery and Characterization.

“This review will 1) highlight what is known about lncRNAs in the context of diabetes, 2) summarize the strategies used in lncRNA discovery pipelines, and 3) discuss future directions and the potential impact of studying the role of lncRNAs in diabetes.”

“Decades of mouse research and advances in genome-wide association studies have identified several genetic drivers of monogenic syndromes of β-cell dysfunction, as well as 113 distinct type 2 diabetes (T2D) susceptibility loci (1) and ∼60 loci associated with an increased risk of developing type 1 diabetes (T1D) (2). Interestingly, these studies discovered that most T1D and T2D susceptibility loci fall outside of coding regions, which suggests a role for noncoding elements in the development of disease (3,4). Several studies have demonstrated that many causal variants of diabetes are significantly enriched in regions containing islet enhancers, promoters, and transcription factor binding sites (5,6); however, not all diabetes susceptibility loci can be explained by associations with these regulatory regions. […] Advances in RNA sequencing (RNA-seq) technologies have revealed that mammalian genomes encode tens of thousands of RNA transcripts that have similar features to mRNAs, yet are not translated into proteins (7). […] detailed characterization of many of these transcripts has challenged the idea that the central role for RNA in a cell is to give rise to proteins. Instead, these RNA transcripts make up a class of molecules called noncoding RNAs (ncRNAs) that function either as “housekeeping” ncRNAs, such as transfer RNAs (tRNAs) and ribosomal RNAs (rRNAs), that are expressed ubiquitously and are required for protein synthesis or as “regulatory” ncRNAs that control gene expression. While the functional mechanisms of short regulatory ncRNAs, such as microRNAs (miRNAs), small interfering RNAs (siRNAs), and Piwi-interacting RNAs (piRNAs), have been described in detail (810), the most abundant and functionally enigmatic regulatory ncRNAs are called long noncoding RNAs (lncRNAs) that are loosely defined as RNAs larger than 200 nucleotides (nt) that do not encode for protein (1113). Although using a definition based strictly on size is somewhat arbitrary, this definition is useful both bioinformatically […] and technically […]. While the 200-nt size cutoff has simplified identification of lncRNAs, this rather broad classification means several features of lncRNAs, including abundance, cellular localization, stability, conservation, and function, are inherently heterogeneous (1517). Although this represents one of the major challenges of lncRNA biology, it also highlights the untapped potential of lncRNAs to provide a novel layer of gene regulation that influences islet physiology and pathophysiology.”

“Although the role of miRNAs in diabetes has been well established (9), analyses of lncRNAs in islets have lagged behind their short ncRNA counterparts. However, several recent studies provide evidence that lncRNAs are crucial components of the islet regulome and may have a role in diabetes (27). […] misexpression of several lncRNAs has been correlated with diabetes complications, such as diabetic nephropathy and retinopathy (2931). There are also preliminary studies suggesting that circulating lncRNAs, such as Gas5, MIAT1, and SENCR, may represent effective molecular biomarkers of diabetes and diabetes-related complications (32,33). Finally, several recent studies have explored the role of lncRNAs in the peripheral metabolic tissues that contribute to energy homeostasis […]. In addition to their potential as genetic drivers and/or biomarkers of diabetes and diabetes complications, lncRNAs can be exploited for the treatment of diabetes. For example, although tremendous efforts have been dedicated to generating replacement β-cells for individuals with diabetes (35,36), human pluripotent stem cell–based β-cell differentiation protocols remain inefficient, and the end product is still functionally and transcriptionally immature compared with primary human β-cells […]. This is largely due to our incomplete knowledge of in vivo differentiation regulatory pathways, which likely include a role for lncRNAs. […] Inherent characteristics of lncRNAs have also made them attractive candidates for drug targeting, which could be exploited for developing new diabetes therapies.”

“With the advancement of high-throughput sequencing techniques, the list of islet-specific lncRNAs is growing exponentially; however, functional characterization is missing for the majority of these lncRNAs. […] Tens of thousands of lncRNAs have been identified in different cell types and model organisms; however, their functions largely remain unknown. Although the tools for determining lncRNA function are technically restrictive, uncovering novel regulatory mechanisms will have the greatest impact on understanding islet function and identifying novel therapeutics for diabetes. To date, no biochemical assay has been used to directly determine the molecular mechanisms by which islet lncRNAs function, which highlights both the infancy of the field and the difficulty in implementing these techniques. […] Due to the infancy of the lncRNA field, most of the biochemical and genetic tools used to interrogate lncRNA function have only recently been developed or are adapted from techniques used to study protein-coding genes and we are only beginning to appreciate the limits and challenges of borrowing strategies from the protein-coding world.”

“The discovery of lncRNAs as a novel class of tissue-specific regulatory molecules has spawned an exciting new field of biology that will significantly impact our understanding of pancreas physiology and pathophysiology. As the field continues to grow, there is growing appreciation that lncRNAs will provide many of the missing components to existing molecular pathways that regulate islet biology and contribute to diabetes when they become dysfunctional. However, to date, most of the experimental emphasis on lncRNAs has focused on large-scale discovery using genome-wide approaches, and there remains a paucity of functional analysis.”

ii. Diabetes and Trajectories of Estimated Glomerular Filtration Rate: A Prospective Cohort Analysis of the Atherosclerosis Risk in Communities Study.

“Diabetes is among the strongest common risk factors for end-stage renal disease, and in industrialized countries, diabetes contributes to ∼50% of cases (3). Less is known about the pattern of kidney function decline associated with diabetes that precedes end-stage renal disease. Identifying patterns of estimated glomerular filtration rate (eGFR) decline could inform monitoring practices for people at high risk of chronic kidney disease (CKD) progression. A better understanding of when and in whom eGFR decline occurs would be useful for the design of clinical trials because eGFR decline >30% is now often used as a surrogate end point for CKD progression (4). Trajectories among persons with diabetes are of particular interest because of the possibility for early intervention and the prevention of CKD development. However, eGFR trajectories among persons with new diabetes may be complex due to the hypothesized period of hyperfiltration by which GFR increases, followed by progressive, rapid decline (5). Using data from the Atherosclerosis Risk in Communities (ARIC) study, an ongoing prospective community-based cohort of >15,000 participants initiated in 1987 with serial measurements of creatinine over 26 years, our aim was to characterize patterns of eGFR decline associated with diabetes, identify demographic, genetic, and modifiable risk factors within the population with diabetes that were associated with steeper eGFR decline, and assess for evidence of early hyperfiltration.”

“We categorized people into groups of no diabetes, undiagnosed diabetes, and diagnosed diabetes at baseline (visit 1) and compared baseline clinical characteristics using ANOVA for continuous variables and Pearson χ2 tests for categorical variables. […] To estimate individual eGFR slopes over time, we used linear mixed-effects models with random intercepts and random slopes. These models were fit on diabetes status at baseline as a nominal variable to adjust the baseline level of eGFR and included an interaction term between diabetes status at baseline and time to estimate annual decline in eGFR by diabetes categories. Linear mixed models were run unadjusted and adjusted, with the latter model including the following diabetes and kidney disease–related risk factors: age, sex, race–center, BMI, systolic blood pressure, hypertension medication use, HDL, prevalent coronary heart disease, annual family income, education status, and smoking status, as well as each variable interacted with time. Continuous covariates were centered at the analytic population mean. We tested model assumptions and considered different covariance structures, comparing nested models using Akaike information criteria. We identified the unstructured covariance model as the most optimal and conservative approach. From the mixed models, we described the overall mean annual decline by diabetes status at baseline and used the random effects to estimate best linear unbiased predictions to describe the distributions of yearly slopes in eGFR by diabetes status at baseline and displayed them using kernel density plots.”

“Because of substantial variation in annual eGFR slope among people with diagnosed diabetes, we sought to identify risk factors that were associated with faster decline. Among those with diagnosed diabetes, we compared unadjusted and adjusted mean annual decline in eGFR by race–APOL1 risk status (white, black– APOL1 low risk, and black–APOL1 high risk) [here’s a relevant link, US], systolic blood pressure […], smoking status […], prevalent coronary heart disease […], diabetes medication use […], HbA1c […], and 1,5-anhydroglucitol (≥10 and <10 μg/mL) [relevant link, US]. Because some of these variables were only available at visit 2, we required that participants included in this subgroup analysis attend both visits 1 and 2 and not be missing information on APOL1 or the variables assessed at visit 2 to ensure a consistent sample size. In addition to diabetes and kidney disease–related risk factors in the adjusted model, we also included diabetes medication use and HbA1c to account for diabetes severity in these analyses. […] to explore potential hyperfiltration, we used a linear spline model to allow the slope to change for each diabetes category between the first 3 years of follow-up (visit 1 to visit 2) and the subsequent time period (visit 2 to visit 5).”

“There were 15,517 participants included in the analysis: 13,698 (88%) without diabetes, 634 (4%) with undiagnosed diabetes, and 1,185 (8%) with diagnosed diabetes at baseline. […] At baseline, participants with undiagnosed and diagnosed diabetes were older, more likely to be black or have hypertension and coronary heart disease, and had higher mean BMI and lower mean HDL compared with those without diabetes […]. Income and education levels were also lower among those with undiagnosed and diagnosed diabetes compared with those without diabetes. […] Overall, there was a nearly linear association between eGFR and age over time, regardless of diabetes status […]. The crude mean annual decline in eGFR was slowest among those without diabetes at baseline (decline of −1.6 mL/min/1.73 m2/year [95% CI −1.6 to −1.5]), faster among those with undiagnosed diabetes compared with those without diabetes (decline of −2.1 mL/min/1.73 m2/year [95% CI −2.2 to −2.0][…]), and nearly twice as rapid among those with diagnosed diabetes compared with those without diabetes (decline of −2.9 mL/min/1.73 m2/year [95% CI −3.0 to −2.8][…]). Adjustment for diabetes and kidney disease–related risk factors attenuated the results slightly, but those with undiagnosed and diagnosed diabetes still had statistically significantly steeper declines than those without diabetes (decline among no diabetes −1.4 mL/min/1.73 m2/year [95% CI −1.5 to −1.4] and decline among undiagnosed diabetes −1.8 mL/min/1.73 m2/year [95% CI −2.0 to −1.7], difference vs. no diabetes of −0.4 mL/min/1.73 m2/year [95% CI −0.5 to −0.3; P < 0.001]; decline among diagnosed diabetes −2.5 mL/min/1.73 m2/year [95% CI −2.6 to −2.4], difference vs. no diabetes of −1.1 mL/min/1.73 m2/ year [95% CI −1.2 to −1.0; P < 0.001]). […] The decline in eGFR per year varied greatly across individuals, particularly among those with diabetes at baseline […] Among participants with diagnosed diabetes at baseline, those who were black, had systolic blood pressure ≥140 mmHg, used diabetes medications, had an HbA1c ≥7% [≥53 mmol/mol], or had 1,5-anhydroglucitol <10 μg/mL were at risk for steeper annual declines than their counterparts […]. Smoking status and prevalent coronary heart disease were not associated with significantly steeper eGFR decline in unadjusted analyses. Adjustment for risk factors, diabetes medication use, and HbA1c attenuated the differences in decline for all subgroups with the exception of smoking status, leaving black race along with APOL1-susceptible genotype, systolic blood pressure ≥140 mmHg, current smoking, insulin use, and HbA1c ≥9% [≥75 mmol/mol] as the risk factors indicative of steeper decline.”

CONCLUSIONS Diabetes is an important risk factor for kidney function decline. Those with diagnosed diabetes declined almost twice as rapidly as those without diabetes. Among people with diagnosed diabetes, steeper declines were seen in those with modifiable risk factors, including hypertension and glycemic control, suggesting areas for continued targeting in kidney disease prevention. […] Few other community-based studies have evaluated differences in kidney function decline by diabetes status over a long period through mid- and late life. One study of 10,184 Canadians aged ≥66 years with creatinine measured during outpatient visits showed results largely consistent with our findings but with much shorter follow-up (median of 2 years) (19). Other studies of eGFR change in a general population have found smaller declines than our results (20,21). A study conducted in Japanese participants aged 40–79 years found a decline of only −0.4 mL/min/1.73 m2/year over the course of two assessments 10 years apart (compared with our estimate among those without diabetes: −1.6 mL/min/1.73 m2/year). This is particularly interesting, as Japan is known to have a higher prevalence of CKD and end-stage renal disease than the U.S. (20). However, this study evaluated participants over a shorter time frame and required attendance at both assessments, which may have decreased the likelihood of capturing severe cases and resulted in underestimation of decline.”

“The Baltimore Longitudinal Study of Aging also assessed kidney function over time in a general population of 446 men, ranging in age from 22 to 97 years at baseline, each with up to 14 measurements of creatinine clearance assessed between 1958 and 1981 (21). They also found a smaller decline than we did (−0.8 mL/min/year), although this study also had notable differences. Their main analysis excluded participants with hypertension and history of renal disease or urinary tract infection and those treated with diuretics and/or antihypertensive medications. Without those exclusions, their overall estimate was −1.1 mL/min/year, which better reflects a community-based population and our results. […] In our evaluation of risk factors that might explain the variation in decline seen among those with diagnosed diabetes, we observed that black race, systolic blood pressure ≥140 mmHg, insulin use, and HbA1c ≥9% (≥75 mmol/mol) were particularly important. Although the APOL1 high-risk genotype is a known risk factor for eGFR decline, African Americans with low-risk APOL1 status continued to be at higher risk than whites even after adjustment for traditional risk factors, diabetes medication use, and HbA1c.”

“Our results are relevant to the design and conduct of clinical trials. Hard clinical outcomes like end-stage renal disease are relatively rare, and a 30–40% decline in eGFR is now accepted as a surrogate end point for CKD progression (4). We provide data on patient subgroups that may experience accelerated trajectories of kidney function decline, which has implications for estimating sample size and ensuring adequate power in future clinical trials. Our results also suggest that end points of eGFR decline might not be appropriate for patients with new-onset diabetes, in whom declines may actually be slower than among persons without diabetes. Slower eGFR decline among those with undiagnosed diabetes, who are likely early in the course of diabetes, is consistent with the hypothesis of hyperfiltration. Similar to other studies, we found that persons with undiagnosed diabetes had higher GFR at the outset, but this was a transient phenomenon, as they ultimately experienced larger declines in kidney function than those without diabetes over the course of follow-up (2325). Whether hyperfiltration is a universal aspect of early disease and, if not, whether it portends worse long-term outcomes is uncertain. Existing studies investigating hyperfiltration as a precursor to adverse kidney outcomes are inconsistent (24,26,27) and often confounded by diabetes severity factors like duration (27). We extended this literature by separating undiagnosed and diagnosed diabetes to help address that confounding.”

iii. Saturated Fat Is More Metabolically Harmful for the Human Liver Than Unsaturated Fat or Simple Sugars.

OBJECTIVE Nonalcoholic fatty liver disease (i.e., increased intrahepatic triglyceride [IHTG] content), predisposes to type 2 diabetes and cardiovascular disease. Adipose tissue lipolysis and hepatic de novo lipogenesis (DNL) are the main pathways contributing to IHTG. We hypothesized that dietary macronutrient composition influences the pathways, mediators, and magnitude of weight gain-induced changes in IHTG.

RESEARCH DESIGN AND METHODS We overfed 38 overweight subjects (age 48 ± 2 years, BMI 31 ± 1 kg/m2, liver fat 4.7 ± 0.9%) 1,000 extra kcal/day of saturated (SAT) or unsaturated (UNSAT) fat or simple sugars (CARB) for 3 weeks. We measured IHTG (1H-MRS), pathways contributing to IHTG (lipolysis ([2H5]glycerol) and DNL (2H2O) basally and during euglycemic hyperinsulinemia), insulin resistance, endotoxemia, plasma ceramides, and adipose tissue gene expression at 0 and 3 weeks.

RESULTS Overfeeding SAT increased IHTG more (+55%) than UNSAT (+15%, P < 0.05). CARB increased IHTG (+33%) by stimulating DNL (+98%). SAT significantly increased while UNSAT decreased lipolysis. SAT induced insulin resistance and endotoxemia and significantly increased multiple plasma ceramides. The diets had distinct effects on adipose tissue gene expression.”

CONCLUSIONS NAFLD has been shown to predict type 2 diabetes and cardiovascular disease in multiple studies, even independent of obesity (1), and also to increase the risk of progressive liver disease (17). It is therefore interesting to compare effects of different diets on liver fat content and understand the underlying mechanisms. We examined whether provision of excess calories as saturated (SAT) or unsaturated (UNSAT) fats or simple sugars (CARB) influences the metabolic response to overfeeding in overweight subjects. All overfeeding diets increased IHTGs. The SAT diet induced a greater increase in IHTGs than the UNSAT diet. The composition of the diet altered sources of excess IHTGs. The SAT diet increased lipolysis, whereas the CARB diet stimulated DNL. The SAT but not the other diets increased multiple plasma ceramides, which increase the risk of cardiovascular disease independent of LDL cholesterol (18). […] Consistent with current dietary recommendations (3638), the current study shows that saturated fat is the most harmful dietary constituent regarding IHTG accumulation.”

iv. Primum Non Nocere: Refocusing Our Attention on Severe Hypoglycemia Prevention.

“Severe hypoglycemia, defined as low blood glucose requiring assistance for recovery, is arguably the most dangerous complication of type 1 diabetes as it can result in permanent cognitive impairment, seizure, coma, accidents, and death (1,2). Since the Diabetes Control and Complications Trial (DCCT) demonstrated that intensive intervention to normalize glucose prevents long-term complications but at the price of a threefold increase in the rate of severe hypoglycemia (3), hypoglycemia has been recognized as the major limitation to achieving tight glycemic control. Severe hypoglycemia remains prevalent among adults with type 1 diabetes, ranging from ∼1.4% per year in the DCCT/EDIC (Epidemiology of Diabetes Interventions and Complications) follow-up cohort (4) to ∼8% in the T1D Exchange clinic registry (5).

One the greatest risk factors for severe hypoglycemia is impaired awareness of hypoglycemia (6), which increases risk up to sixfold (7,8). Hypoglycemia unawareness results from deficient counterregulation (9), where falling glucose fails to activate the autonomic nervous system to produce neuroglycopenic symptoms that normally help patients identify and respond to episodes (i.e., sweating, palpitations, hunger) (2). An estimated 20–25% of adults with type 1 diabetes have impaired hypoglycemia awareness (8), which increases to more than 50% after 25 years of disease duration (10).

Screening for hypoglycemia unawareness to identify patients at increased risk of severe hypoglycemic events should be part of routine diabetes care. Self-identified impairment in awareness tends to agree with clinical evaluation (11). Therefore, hypoglycemia unawareness can be easily and effectively screened […] Interventions for hypoglycemia unawareness include a range of behavioral and medical options. Avoiding hypoglycemia for at least several weeks may partially reverse hypoglycemia unawareness and reduce risk of future episodes (1). Therefore, patients with hypoglycemia and unawareness may be advised to raise their glycemic and HbA1c targets (1,2). Diabetes technology can play a role, including continuous subcutaneous insulin infusion (CSII) to optimize insulin delivery, continuous glucose monitoring (CGM) to give technological awareness in the absence of symptoms (14), or the combination of the two […] Aside from medical management, structured or hypoglycemia-specific education programs that aim to prevent hypoglycemia are recommended for all patients with severe hypoglycemia or hypoglycemia unawareness (14). In randomized trials, psychoeducational programs that incorporate increased education, identification of personal risk factors, and behavior change support have improved hypoglycemia unawareness and reduced the incidence of both nonsevere and severe hypoglycemia over short periods of follow-up (17,18) and extending up to 1 year (19).”

“Given that the presence of hypoglycemia unawareness increases the risk of severe hypoglycemia, which is the strongest predictor of a future episode (2,4), the implication that intervention can break the life-threatening and traumatizing cycle of hypoglycemia unawareness and severe hypoglycemia cannot be overstated. […] new evidence of durability of effect across treatment regimen without increasing the risk for long-term complications creates an imperative for action. In combination with existing screening tools and a body of literature investigating novel interventions for hypoglycemia unawareness, these results make the approach of screening, recognition, and intervention very compelling as not only a best practice but something that should be incorporated in universal guidelines on diabetes care, particularly for individuals with type 1 diabetes […] Hyperglycemia is […] only part of the puzzle in diabetes management. Long-term complications are decreasing across the population with improved interventions and their implementation (24). […] it is essential to shift our historical obsession with hyperglycemia and its long-term complications to equally emphasize the disabling, distressing, and potentially fatal near-term complication of our treatments, namely severe hypoglycemia. […] The health care providers’ first dictum is primum non nocere — above all, do no harm. ADA must refocus our attention on severe hypoglycemia as an iatrogenic and preventable complication of our interventions.”

v. Anti‐vascular endothelial growth factor combined with intravitreal steroids for diabetic macular oedema.

“Background

The combination of steroid and anti‐vascular endothelial growth factor (VEGF) intravitreal therapeutic agents could potentially have synergistic effects for treating diabetic macular oedema (DMO). On the one hand, if combined treatment is more effective than monotherapy, there would be significant implications for improving patient outcomes. Conversely, if there is no added benefit of combination therapy, then people could be potentially exposed to unnecessary local or systemic side effects.

Objectives

To assess the effects of intravitreal agents that block vascular endothelial growth factor activity (anti‐VEGF agents) plus intravitreal steroids versus monotherapy with macular laser, intravitreal steroids or intravitreal anti‐VEGF agents for managing DMO.”

“There were eight RCTs (703 participants, 817 eyes) that met our inclusion criteria with only three studies reporting outcomes at one year. The studies took place in Iran (3), USA (2), Brazil (1), Czech Republic (1) and South Korea (1). […] When comparing anti‐VEGF/steroid with anti‐VEGF monotherapy as primary therapy for DMO, we found no meaningful clinical difference in change in BCVA [best corrected visual acuity] […] or change in CMT [central macular thickness] […] at one year. […] There was very low‐certainty evidence on intraocular inflammation from 8 studies, with one event in the anti‐VEGF/steroid group (313 eyes) and two events in the anti‐VEGF group (322 eyes). There was a greater risk of raised IOP (Peto odds ratio (OR) 8.13, 95% CI 4.67 to 14.16; 635 eyes; 8 RCTs; moderate‐certainty evidence) and development of cataract (Peto OR 7.49, 95% CI 2.87 to 19.60; 635 eyes; 8 RCTs; moderate‐certainty evidence) in eyes receiving anti‐VEGF/steroid compared with anti‐VEGF monotherapy. There was low‐certainty evidence from one study of an increased risk of systemic adverse events in the anti‐VEGF/steroid group compared with the anti‐VEGF alone group (Peto OR 1.32, 95% CI 0.61 to 2.86; 103 eyes).”

“One study compared anti‐VEGF/steroid versus macular laser therapy. At one year investigators did not report a meaningful difference between the groups in change in BCVA […] or change in CMT […]. There was very low‐certainty evidence suggesting an increased risk of cataract in the anti‐VEGF/steroid group compared with the macular laser group (Peto OR 4.58, 95% 0.99 to 21.10, 100 eyes) and an increased risk of elevated IOP in the anti‐VEGF/steroid group compared with the macular laser group (Peto OR 9.49, 95% CI 2.86 to 31.51; 100 eyes).”

“Authors’ conclusions

Combination of intravitreal anti‐VEGF plus intravitreal steroids does not appear to offer additional visual benefit compared with monotherapy for DMO; at present the evidence for this is of low‐certainty. There was an increased rate of cataract development and raised intraocular pressure in eyes treated with anti‐VEGF plus steroid versus anti‐VEGF alone. Patients were exposed to potential side effects of both these agents without reported additional benefit.”

vi. Association between diabetic foot ulcer and diabetic retinopathy.

“More than 25 million people in the United States are estimated to have diabetes mellitus (DM), and 15–25% will develop a diabetic foot ulcer (DFU) during their lifetime [1]. DFU is one of the most serious and disabling complications of DM, resulting in significantly elevated morbidity and mortality. Vascular insufficiency and associated neuropathy are important predisposing factors for DFU, and DFU is the most common cause of non-traumatic foot amputation worldwide. Up to 70% of all lower leg amputations are performed on patients with DM, and up to 85% of all amputations are preceded by a DFU [2, 3]. Every year, approximately 2–3% of all diabetic patients develop a foot ulcer, and many require prolonged hospitalization for the treatment of ensuing complications such as infection and gangrene [4, 5].

Meanwhile, a number of studies have noted that diabetic retinopathy (DR) is associated with diabetic neuropathy and microvascular complications [610]. Despite the magnitude of the impact of DFUs and their consequences, little research has been performed to investigate the characteristics of patients with a DFU and DR. […] the aim of this study was to investigate the prevalence of DR in patients with a DFU and to elucidate the potential association between DR and DFUs.”

“A retrospective review was conducted on DFU patients who underwent ophthalmic and vascular examinations within 6 months; 100 type 2 diabetic patients with DFU were included. The medical records of 2496 type 2 diabetic patients without DFU served as control data. DR prevalence and severity were assessed in DFU patients. DFU patients were compared with the control group regarding each clinical variable. Additionally, DFU patients were divided into two groups according to DR severity and compared. […] Out of 100 DFU patients, 90 patients (90%) had DR and 55 (55%) had proliferative DR (PDR). There was no significant association between DR and DFU severities (R = 0.034, p = 0.734). A multivariable analysis comparing type 2 diabetic patients with and without DFUs showed that the presence of DR [OR, 226.12; 95% confidence interval (CI), 58.07–880.49; p < 0.001] and proliferative DR [OR, 306.27; 95% CI, 64.35–1457.80; p < 0.001), higher HbA1c (%, OR, 1.97, 95% CI, 1.46–2.67; p < 0.001), higher serum creatinine (mg/dL, OR, 1.62, 95% CI, 1.06–2.50; p = 0.027), older age (years, OR, 1.12; 95% CI, 1.06–1.17; p < 0.001), higher pulse pressure (mmHg, OR, 1.03; 95% CI, 1.00–1.06; p = 0.025), lower cholesterol (mg/dL, OR, 0.94; 95% CI, 0.92–0.97; p < 0.001), lower BMI (kg/m2, OR, 0.87, 95% CI, 0.75–1.00; p = 0.044) and lower hematocrit (%, OR, 0.80, 95% CI, 0.74–0.87; p < 0.001) were associated with DFUs. In a subgroup analysis of DFU patients, the PDR group had a longer duration of diabetes mellitus, higher serum BUN, and higher serum creatinine than the non-PDR group. In the multivariable analysis, only higher serum creatinine was associated with PDR in DFU patients (OR, 1.37; 95% CI, 1.05–1.78; p = 0.021).

Conclusions

Diabetic retinopathy is prevalent in patients with DFU and about half of DFU patients had PDR. No significant association was found in terms of the severity of these two diabetic complications. To prevent blindness, patients with DFU, and especially those with high serum creatinine, should undergo retinal examinations for timely PDR diagnosis and management.”

August 29, 2018 Posted by | Diabetes, Epidemiology, Genetics, Medicine, Molecular biology, Nephrology, Ophthalmology, Statistics, Studies | Leave a comment

Nephrology Board Review

Some links related to the lecture’s coverage:

Diabetic nephropathy.
Henoch–Schönlein purpura.
Leukocytoclastic Vasculitis.
Glomerulonephritis. Rapidly progressive glomerulonephritis.
Nephrosis.
Analgesic nephropathy.
Azotemia.
Allergic Interstitial Nephritis: Clinical Features and Pathogenesis.
Nonsteroidal anti-inflammatory drugs: effects on kidney function (Whelton & Hamilton, J Clin Pharmacol. 1991 Jul;31(7):588-98).
Goodpasture syndrome.
Creatinine. Limitations of serum creatinine as a marker of renal function.
Hyperkalemia.
U wave.
Nephrolithiasis. Calcium oxalate.
Calcium gluconate.
Bicarbonate.
Effect of various therapeutic approaches on plasma potassium and major regulating factors in terminal renal failure (Blumberg et al., 1988).
Effect of prolonged bicarbonate administration on plasma potassium in terminal renal failure (Blumberg et al., 1992).
Renal tubular acidosis.
Urine anion gap.
Metabolic acidosis.
Contrast-induced nephropathy.
Rhabdomyolysis.
Lipiduria. Urinary cast.
Membranous glomerulonephritis.
Postinfectious glomerulonephritis.

August 28, 2018 Posted by | Cardiology, Chemistry, Diabetes, Lectures, Medicine, Nephrology, Pharmacology, Studies | Leave a comment

100 Cases in Orthopaedics and Rheumatology (II)

Below I have added some links related to the last half of the book’s coverage, as well as some more observations from the book.

Scaphoid fracture. Watson’s test. Dorsal intercalated segment instability. (“Non-union is not uncommon as a complication after scaphoid fractures because the blood supply to this bone is poor. Smokers have a higher incidence of non-union. Occasionally, the blood supply is poor enough to lead to avascular necrosis. If non-union is not detected, subsequent arthritis in the wrist can develop.”)
Septic arthritis. (“Septic arthritis is an orthopaedic emergency. […] People with septic arthritis are typically unwell with fevers and malaise and the joint pain is severe. […] Any acutely hot or painful joint is septic arthritis until proven otherwise.”)
Rheumatoid arthritis. (“[RA is] the most common of the inflammatory arthropathies. […] early-morning stiffness and pain, combined with soft-tissue rather than bony swelling, are classic patterns for inflammatory disease. Although […] RA affects principally the small joints of the hands (and feet), it may progress to involve any synovial joint and may be complicated by extra-articular features […] family history [of the disease] is not unusual due to the presence of susceptibility genes such as HLA-DR. […] Not all patients with RA have rheumatoid factor (RF), and not all patients with RF have RA; ACPA has greater specificity for RA than rheumatoid factor. […] Medical therapy focuses on disease-modifying anti-rheumatic drugs (DMARDs) such as methotrexate, sulphasalazine, leflunomide and hydroxychloroquine which may be used individually or in combination. […] Disease activity in RA is measured by the disease activity score (DAS), which is a composite score of the clinical evidence of synovitis, the current inflammatory response and the patient’s own assessment of their health. […] Patients who have high disease activity as determined by the DAS and have either failed or failed to tolerate standard disease modifying therapy qualify for biologic therapy – monoclonal antibodies that are directed against key components of the inflammatory response. […] TNF-α blockade is highly effective in up to 70 per cent of patients, reducing both inflammation and the progressive structural damage associated with severe active disease.”)
Ankylosing spondylitis. Ankylosis. Schober’s index. Costochondritis.
Mononeuritis multiplex. (“Mononeuritis multiplex arises due to interruption of the vasa nervorum, the blood supply to peripheral nerves […] Mononeuritis multiplex is commonly caused by diabetes or vasculitis. […] Vasculitis – inflammation of blood vessels and subsequent obstruction to blood flow – can be primary (idiopathic) or secondary, in which case it is associated with an underlying condition such as rheumatoid arthritis. The vasculitides are classified according to the size of the vessel involved. […] Management of mononeuritis multiplex is based on potent immunosuppression […] and the treatment of underlying infections such as hepatitis.”)
Multiple myeloma. Bence-Jones protein. (“The combination of bone pain and elevated ESR and calcium is suggestive of multiple myeloma.”)
Osteoporosis. DEXA scan. T-score. (“Postmenopausal bone loss is the most common cause of osteoporosis, but secondary osteoporosis may occur in the context of a number of medical conditions […] Steroid-induced osteoporosis is a significant problem in medical practice. […] All patients receiving corticosteroids should have bone protection […] Pharmacological treatment in the form of calcium supplementation and biphosphonates to reduce osteoclast activity is effective but compliance is typically poor.”)
Osteomalacia. Rickets. Craniotabes.
Paget’s disease (see also this post). (“In practical terms, the main indication to treat Paget’s disease is pain […] although bone deformity or compression syndromes (or risk thereof) would also prompt therapy. The treatment of choice is a biphosphonate to diminish osteoclast activity”).
Stress fracture. Female athlete triad. (“Stress fractures are overuse injuries and occur when periosteal resorption exceeds bone formation. They are commonly seen in two main patient groups: soldiers may suffer so-called march fractures in the metatarsals, while athletes may develop them in different sites according to their sporting activity. Although the knee is a common site in runners due to excess mechanical loading, stress fractures may also result in non-weight-bearing sites due to repetitive and excessive traction […]. The classic symptom […] is of pain that occurs throughout running and crucially persists with rest; this is in contrast to shin splints, a traction injury to the tibial periosteum in which the pain diminishes somewhat with continued activity […] The crucial feature of rehabilitation is a graded return to sport to prevent progression or recurrence.”)
Psoriatic arthritis. (“Arthropathy and rash is a common combination in rheumatology […] Psoriatic arthritis is a common inflammatory arthropathy that affects up to 15 per cent of those with psoriasis. […] Nail disease is very helpful in differentiating psoriatic arthritis from other forms of inflammatory arthropathy.”)
Ehlers–Danlos syndromes. Marfan syndrome. Beighton (hypermobility) score.
Carpal tunnel syndrome. (“Carpal tunnel syndrome is the most common entrapment neuropathy […] The classic symptoms are of tingling in the sensory distribution of the median nerve (i.e. the lateral three and a half digits); loss of thumb abduction is a late feature. Symptoms are often worse at night (when the hand might be quite painful) and in certain postures […] The majority of cases are idiopathic, but pregnancy and rheumatoid arthritis are very common precipitating causes […] The majority of patients will respond well to conservative management […] If these measures fail, corticosteroid injection into the carpal tunnel can be very effective in up to 80 per cent of patients. Surgical decompression should be reserved for those with persistent disabling symptoms or motor loss.”)
Mixed connective tissue disease.
Crystal arthropathy. Tophus. Uric acid nephropathyChondrocalcinosis. (“In any patient presenting with an acutely painful and swollen joint, the most important diagnoses to consider are septic arthritis and crystal arthropathy. Crystal arthropathy such as gout is more common than septic arthritis […] Gout may be precipitated by diuretics, renal impairment and aspirin use”).
Familial Mediterranean fever. Amyloidosis.
Systemic lupus erythematosus (see also this). Jaccoud arthropathy. Lupus nephritis. (“Renal disease is the most feared complication of SLE.”)
Scleroderma. Raynaud’s phenomenon. (“Scleroderma is an uncommon disorder characterized by thickening of the skin and, to a greater or lesser degree, fibrosis of internal organs.”)
Henoch-Schönlein purpura. Cryoglobulinemia. (“Purpura are the result of a spontaneous extravasation of blood from the capillaries into the skin. If small they are known as petechiae, when they are large they are termed ecchymoses. There is an extensive differential diagnosis for purpura […] The combination of palpable purpura (distributed particularly over the buttocks and extensor surfaces of legs), abdominal pain, arthritis and renal disease is a classic presentation of Henoch–Schönlein purpura (HSP). HSP is a distinct and frequently self-limiting small-vessel vasculitis that can affect any age; but the majority of cases present in children aged 2–10 years, in whom the prognosis is more benign than the adult form, often remitting entirely within 3–4 months. The abdominal pain may mimic a surgical abdomen and can presage intussusception, haemorrhage or perforation. The arthritis, in contrast, is relatively mild and tends to affect the knees and ankles.”)
Rheumatic fever.
Erythema nodosum. (“Mild idiopathic erythema nodosum […] needs no specific treatment”).
Rheumatoid lung disease. Bronchiolitis obliterans. Methotrexate-induced pneumonitis. Hamman–Rich syndrome.
Antiphospholipid syndrome. Sapporo criteria. (“Antiphospholipid syndrome is a hypercoagulable state characterized by recurrent arteriovenous thrombosis and/or pregnancy morbidity in the presence of either a lupus anticoagulant or anticardiolipin antibody (both phospholipid-related proteins). […] The most common arteriovenous thrombotic events in antiphospholipid syndrome are deep venous thrombosis and pulmonary embolus […], but any part of the circulation may be involved, with arterial events such as myocardial infarction and stroke carrying a high mortality rate. Poor placental circulation is thought to be responsible for the high pregnancy morbidity, with recurrent first- and second-trimester loss and a higher rate of pre-eclampsia being typical clinical features.”)
Still’s disease. (“Consider inflammatory disease in cases of pyrexia of unknown origin.”)
Polymyalgia rheumatica. Giant cell arteritis. (“[P]olymyalgia rheumatica (PMR) [is] a systemic inflammatory syndrome affecting the elderly that is characterized by bilateral pain and stiffness in the shoulders and hip girdles. The stiffness can be profound and limits mobility although true muscle weakness is not a feature. […] The affected areas are diffusely tender, with movements limited by pain. […] care must be taken not to attribute joint inflammation to PMR until other diagnoses have been excluded; for example, a significant minority of RA patients may present with a polymyalgic onset. […] The treatment for PMR is low-dose corticosteroids. […] Many physicians would consider a dramatic response to low-dose prednisolone as almost diagnostic for PMR, so if a patients symptoms do not improve rapidly it is wise to re-evaluate the original diagnosis.”)
Relapsing polychondritis. (“Relapsing polychondritis is characterized histologically by inflammatory infiltration and later fibrosis of cartilage. Any cartilage, in any location, is at risk. […] Treatment of relapsing polychondritis is with corticosteroids […] Surgical reconstruction of collapsed structures is not an option as the deformity tends to continue postoperatively.”)
Dermatomyositis. Gottron’s Papules.
Enteropathic arthritis. (“A seronegative arthritis may develop in up to 15 per cent of patients with any form of inflammatory bowel disease, including ulcerative colitis (UC), Crohn’s disease or microscopic and collagenous colitis. The most common clinical presentations are a peripheral arthritis […] and spondyloarthritis.”)
Reflex sympathetic dystrophy.
Whipple’s disease. (“Although rare, consider Whipple’s disease in any patient presenting with malabsorption, weight loss and arthritis.”)
Wegener’s granulomatosis. (“Small-vessel vasculitis may cause a pulmonary-renal syndrome. […] The classic triad of Weneger’s granulomatosis is the presence of upper and lower respiratory tract disease and renal impairment.”)
Reactive arthritis. Reiter’s syndrome. (“Consider reactive arthritis in any patient presenting with a monoarthropathy. […] Reactive arthritis is generally benign, with up to 80 per cent making a full recovery.”)
Sarcoidosis. Löfgren syndrome.
Polyarteritis nodosa. (“Consider mesenteric ischaemia in any patient presenting with a systemic illness and postprandial abdominal pain.”)
Sjögren syndrome. Schirmer’s test.
Behçet syndrome.
Lyme disease. Erythema chronicum migrans. (“The combination of rash leading to arthralgia and cranial neuropathy is a classic presentation of Lyme disease.”)
Takayasu arteritis. (“Takayasu’s arteritis is an occlusive vasculitis leading to stenoses of the aorta and its principal branches. The symptoms and signs of the disease depend on the distribution of the affected vessel but upper limbs are generally affected more commonly than the iliac tributaries. […] the disease is a chronic relapsing and remitting condition […] The mainstay of treatment is high-dose corticosteroids plus a steroid-sparing agent such as methotrexate. […] Cyclophosphamide is reserved for those patients who do not achieve remission with standard therapy. Surgical intervention such as bypass or angioplasty may improve ischaemic symptoms once the inflammation is under control.”)
Lymphoma.
Haemarthrosis. (“Consider synovial tumours in a patient with unexplained haemarthrosis.”)
Juvenile idiopathic arthritis.
Drug-induced lupus erythematosus. (“Drug-induced lupus (DIL) generates a different spectrum of clinical manifestations from idiopathic disease. DIL is less severe than idiopathic SLE, and nephritis or central nervous system involvement is very rare. […] The most common drugs responsible for a lupus-like syndrome are procainamide, hydralazine, quinidine, isoniazid, methyldopa, chlorpromazine and minocycline. […] Treatment involves stopping the offending medication and the symptoms will gradually resolve.”)
Churg–Strauss syndrome.

July 8, 2018 Posted by | Books, Cancer/oncology, Cardiology, Gastroenterology, Immunology, Medicine, Nephrology, Neurology, Ophthalmology, Pharmacology | Leave a comment

100 cases in emergency medicine and critical care (II)

In this post I’ve added some links to topics covered in the second half of the book, as well as some quotes.

Flexor tenosynovitis. Kanavel’s cardinal signs.
Pelvic Fracture in Emergency Medicine. (“Pelvic injuries may be associated with significant haemorrhage. […] The definitive management of pelvic fractures is surgical.”)
Femur fracture. Girdlestone-Taylor procedure. (“A fall from standing can result in occult cervical spine fractures. If there is any doubt, then the patient should be immobilized and imaged to exclude injury.”)
Anterior Cruciate Ligament Injury. Anterior drawer test. Segond fracture. (“[R]upture of the anterior cruciate ligament (ACL) […] is often seen in younger patients and is associated with high-energy sports such as skiing, football or cycling. […] Take a careful history of all knee injuries including the mechanism of injury and the timing of swelling.”)
Tibial plateau fracture. Schatzker classification of tibial plateau fractures. (“When assessing the older patient with minor trauma resulting in fracture, always investigate the possibility that this may be a pathological fracture (e.g. osteoporosis, malignancy.”))
Ankle Fracture. Maisonneuve fracture.
Acute cholecystitis. Murphy’s sign. Mirizzi syndrome. (“Most patients with gallstones are asymptomatic. However, complications of gallstones range from biliary colic, whereby gallstones irritate or temporarily block the biliary tract, to acute cholecystitis, which is an infection of the gallbladder sometimes due to obstruction of the cystic duct. Gallstones can also become trapped in the common bile duct (choledocholithiasis) causing jaundice and potential ascending cholangitis, which refers to infection of the biliary tree. Ascending cholangitis classically presents with Charcot’s triad of fever, right upper quadrant (RUQ) pain and jaundice. It can be life-threatening. […] Acute cholecystitis requires antibiotic therapy and admission under general surgery, who should decide whether to perform a ‘hot’ emergency cholecystectomy within 24-72 hours of admission. This shortens the hospital stay but can be associated with more surgical complications.”)
Small-Bowel Obstruction. (“SBO is defined as a mechanical obstruction to the passage of contents in the bowel lumen. There can be complete or incomplete obstruction. […] There are many causes of SBO. […] The commonest cause of SBO worldwide is incarcerated herniae, whereas the commonest cause in the Western world is adhesion secondary to previous abdominal surgery. […] A strangulated hernia is […] a surgical emergency associated with a high mortality.”)
Pneumothorax. Flail chest.
Perforated peptic ulcer. (“Immediate onset pain usually signifies a rupture or occlusion of an organ, whereas more insidious onset tends to be infective or inflammatory in origin.” […] A perforated peptic ulcer is a surgical emergency that presents with upper abdominal pain, decreased or absent bowel sounds and signs of septic shock.”)
Diverticulitis.
Acute appendicitisMcBurney’s point. Rovsing’s sign. Psoas signObturator sign. (“The lifetime risk of developing appendicitis is 5-10%, and it is the commonest cause of emergency abdominal surgery in the Western world. […] in appendicitis, pain classically precedes vomiting, whereas the opposite occurs in gastroenteritis. […] Appendicitis is the commonest general surgical emergency in pregnant women and may have an atypical presentation with pain anywhere in the right side of the abdomen […] It is estimated that 25% of appendicitis will perforate 24 hours from the onset of symptoms, and 75% by 48 hours.”)
Abdominal aortic aneurysm. (“A ruptured AAA is a surgical emergency with 100% mortality if not immediately repaired. It classically presents with abdominal pain, pulsatile abdominal mass and hypotension. It should be ruled out in all patients over 65 years of age presenting with abdominal, loin or groin pain, especially if they have risk factors including smoking, hypertension, COPD or peripheral vascular disease. […] Do not be lured into a diagnosis of renal colic in an older patient, without definitive imaging to rule out an AAA rupture.”)
Nephrolithiasis. (“up to 30% of patients with kidney stones have a recurrence within 5 years”)
Acute Otitis Media. Mastoiditis. Bezold’s abscess.
Malignant otitis externa. (“Despite the term ‘malignant’, this is not a cancerous process. Rather, it refers to temporal bone (skull base) osteomyelitis. This is an ENT emergency associated with serious morbidity and mortality including cranial nerve palsies. […] The defining features of MOE are severe otalgia, often exceeding oral analgesics, in the older diabetic patient. Other symptoms such as hearing loss, otorrhoea, vertigo and tinnitus may also be present”)
Post-tonsillectomy hemorrhage. (Post-tonsillectomy bleeding (PTB) is a common but potentially serious complication occurring in around 5%-10% of patients undergoing tonsillectomy. The majority are self-limiting but around 1% require a return to theatre to stop the bleeding. All patients must be assessed immediately and admitted for observation as a self-limiting bleed can preclude a larger bleed within 24 hours. […] [PTB] should be treated as an airway emergency due to the possibility of obstruction.”)
Acute rhinosinusitis. (“Periorbital cellulitis is a potentially sight-threatening emergency. It is often precipitated by an upper respiratory tract infection, rhinosinusitis or local trauma (injury, insect bite).”)
Corneal Foreign Body. Seidel test. (“Pain with photosensitivity, watery discharge and foreign body sensation are cardinal features of corneal irritation. […] Abnormal pupil shape, iris defect and shallow anterior chamber are red flags for possible ocular perforation or penetrating ocular injury. […] Most conjunctival foreign bodies can be removed by simply irrigating the eye […] Removing a corneal foreign body […] requires more skill and an experienced operator should be sought. […] Iron, steel, copper and wood are known to cause severe ocular reactions”)
Acanthamoeba Keratitis. Bacterial Keratitis. Fungal keratitis. (“In patients with red eyes, reduced vision with severe to moderate pain should be prompted to an early ophthalmology review. Pre-existing ocular surface disease and contact lens wear are high risk factors for microbial keratitis.”)
Globe ruptureAcute orbital compartment syndromeLateral Canthotomy and Cantholysis. (Thirty percent of all facial fractures involve the orbit […] In open globe injuries with visible penetrating objects, it may be tempting to remove the object; however, avoid this as it may cause the globe to collapse.”)
Mandibular fracture. Guardsman fracture. (“Jaw pain, altered bite, numbness of lower lip, trismus or difficulty moving the jaw are the cardinal symptoms of possible mandibular fracture or dislocation.”)
Bronchiolitis. (“This is an acute respiratory condition, resulting in inflammation of the bronchioles. […] Bronchiolitis occurs in children under 2 years of age and most commonly presents in infants aged 3 to 6 months. […] Around 3% of all infants under 1 year old are admitted to hospital with bronchiolitis. […] Not all patients require hospital admission.”)
Fever of Unknown Origin. (“Fever is a very common presentation in the Emergency Department, and in the immunocompetent child is usually caused by a simple infection […] it is important to look for concerning features. Tachycardia is a particular feature that should not be ignored […] red-flag signs for serious illness [include:] • Grunting, tachypneoa or other signs of respiratory distress • Mottled, pale skin with cool peripheries […] Irritability […] not responding to social cues • Difficulty to rouse […] Consider Kawasaki disease in fever lasting more than 5 days.”)
Pediatric gastroenteritis. Rotavirus.
Acute Pyelonephritis. (“Female infants have a two- to-fourfold higher prevalence of UTI than male infants”)
Gastroesophageal Reflux Disease. (“Reflux describes the passage of gastric contents into the oesophagus with or without regurgitation and vomiting. This is a very common, normal, physiological process and occurs in 5% of babies up to six times per day. GORD presents when reflux causes troublesome symptoms or complications. This has a prevalence of 10%– 20% […] No investigations are required in the Emergency Department if there is a suspicion of GORD; this is usually a clinical diagnosis alone.”)
Head injury. (“Head injuries are common in children […] Clinical features of concern in head injuries include multiple episodes of vomiting […] significant scalp haematoma, prolonged loss of consciousness, confusion and seizures.”)
Pertussis. (“In the twentieth century, pertussis was one of the most common childhood diseases and a major cause of childhood mortality. Since use of the immunisation began, incidence has decreased more than 75%.”)
Hyperemesis gravidarum. ([HG] is defined as severe or long-lasting nausea and vomiting, appearing for the first time within the first trimester of pregnancy, and is so severe that weight loss, dehydration and electrolyte imbalance may occur. It affects less than 4% of pregnant women, although up to 80% of women suffer from some degree of nausea and vomiting throughout their pregnancy. […] Classically, patents present with a long history of nausea and vomiting that becomes progressively worse, despite treatment with simple antiemetics.”)
Ectopic pregnancy. (“Abdominal pain and collapse with a positive pregnancy test must be treated as a ruptured ectopic pregnancy until proven otherwise. […] In cases where the patient is stable and an intact ectopic is suspected, this is not an emergency and patients can be brought back the next day […] if seen out of hours”)
Recurrent miscarriage. Antiphospholipid syndrome. (“Bleeding in early pregnancy is common and does not necessarily lead to miscarriage.”)
Ovarian torsion. (“Torsion of the ovary and/ or fallopian tube account for between 2.4% and 7.4% of all gynaecological emergencies, and rapid intervention is required in order to preserve ovarian function. […] Ovarian torsion is unfortunately often misdiagnosed due to its non-specific symptoms and lack of diagnostic tools. […] Suspect ovarian torsion in women with severe sudden onset unilateral pelvic pain.”)
Pelvic Inflammatory Disease. Fitz-Hugh–Curtis syndrome.
Ovarian hyperstimulation syndrome. (“OHSS is an iatrogenic complication of fertility treatment with exogenous gonadotrophins to promote oocyte formation. Hyperstimulation of the ovaries leads to ovarian enlargement, and subsequent exposure to human chorionic gonadotrophin (hCG) causes production of proinflammatory mediators, primarily vascular endothelial growth factor (VEGF). The effects of proinflammatory mediators lead to increased vascular permeability and a loss of fluid from intravascular to third space compartments. This gives rise to ascites, pleural effusions and in some cases pericardial effusions. Women with severe OHSS can typically lose up to 20% of their circulating volume in the acute phase […] OHSS patients are also at high risk of developing a thromboembolism […] In conventional IVF, around one-third of cycles are affected by mild OHSS. The combined incidence of moderate or severe OHSS is reported as between 3.1% and 8%.”)
Pulmonary embolism. (“The overall prevalence of PE in pregnancy is between 2% and 6%. Pregnancy increases the risk of developing a venous thromboembolism by four to five times, compared to non-pregnant women of the same age.”)
Postpartum psychosis.
Informed consent. Gillick competency and Fraser guidelines.
Duty of candour. Never events.

May 8, 2018 Posted by | Books, Gastroenterology, Infectious disease, Medicine, Nephrology, Ophthalmology | Leave a comment

100 cases in emergency medicine and critical care (I)

“This book has been written for medical students, doctors and nurse practitioners. One of the best methods of learning is case-based learning. This book presents a hundred such ‘cases’ or ‘patients’ which have been arranged by system. Each case has been written to stand alone […] the focus of each case is to recognise the initial presentation, the underlying pathophysiology, and to understand broad treatment principles.”

I really liked the book; as was also the case for the surgery book I recently read the cases included in these publications are slightly longer than they were in some of the previous publications in the series I’ve read, and I think this makes a big difference in terms of how much you actually get out of each case.

Below I have added some links and quotes related to the first half of the book’s coverage.

Tracheostomy.
Malnutrition (“it is estimated that around a quarter of hospital inpatients are inadequately nourished. This may be due to increased nutritional requirements […], nutritional losses (e.g. malabsorption, vomiting, diarrhoea) or reduced intake […] A patient’s basal energy expenditure is doubled in head injuries and burns.”)
Acute Adult Supraglottitis. (“It is important to appreciate that halving the radius of the airway will increase its resistance by 16 times (Poiseuille’s equation), and hearing stridor means there is around 75% airway obstruction.”)
Out-of-hospital cardiac arrest. (“After successful resuscitation from an OHCA, only 10% of patients will survive to discharge, and many of these individuals will have significant neurologic disability.”)
Bacterial meningitis. (“Meningococcal meningitis has a high mortality, with 10%-15% of patients dying of the disease despite appropriate therapy.”)
Diabetic ketoacidosis.
Anaphylaxis (“Always think of anaphylaxis when seeing patients with skin/mucosal symptoms, respiratory difficulty and/or hypotension, especially after exposure to a potential allergen.”)
Early goal-directed therapy. (“While randomised evidence on the benefit of [this approach] is conflicting, it is standard practice in most centres.” I’m not sure I’d agree with the authors that the evidence is ‘conflicting’, it looks to me like it’s reasonably clear at this point: “In this meta-analysis of individual patient data, EGDT did not result in better outcomes than usual care and was associated with higher hospitalization costs across a broad range of patient and hospital characteristics.”)
Cardiac tamponade. Hypovolaemic shock. Permissive hypotensionFocused Assessment with Sonography in Trauma (FAST). (“Shock refers to inadequate tissue perfusion and tissue oxygenation. The commonest cause in an injured patient is hypovolaemic shock due to blood loss, but other causes include cardiogenic shock due to myocardial dysfunction, neurogenic shock due to sympathetic dysfunction or obstructive shock due to obstruction of the great vessels or heart. […] tachycardia, cool skin and reduced pulse pressure are early signs of shock until proven otherwise.”)
Intravenous therapy. A Comparison of Albumin and Saline for Fluid Resuscitation in the Intensive Care Unit.
Thermal burns. Curling’s ulcer. Escharotomy. Wallace rule of nines. Fluid management in major burn injuries. (“Alkali burns are more harmful than acidic. […] Electrical burns cause more destruction than the external burn may suggest. They are associated with internal destruction, as the path of least resistance is nerves and blood vessels. They can also cause arrhythmias and an electrocardiogram should be performed.”)
Steven Johnson syndrome. Nikolsky’s sign. SCORTEN scale.
Cardiac arrest. (“The mantra in the ED is that ‘you are not dead until you are warm and dead'”).
Myocardial infarction. (“The most important goal of the acute management of STEMI is coronary reperfusion, which may be achieved either by percutaneous coronary intervention (PCI) or use of fibrinolytic agents (thrombolysis). PCI is the preferred strategy if it can be delivered within 120 minutes of first medical contact (and ideally within 90 minutes) […] several randomised trials have shown that PCI provides improved short- and long-term survival outcomes compared to fibrinolysis, providing it can be performed within the appropriate time frame.”)
Asthma exacerbation. (“the prognosis for asthmatics admitted to the Intensive Care Unit is guarded, with an in-hospital mortality of 7% in those who are mechanically ventilated.”)
Acute exacerbation of COPD. Respiratory Failure.
Pulmonary embolism. CT pulmonary angiography. (“Obstructive cardiopulmonary disease is the main diagnosis to exclude in patients presenting with shortness of breath and syncope.”)
Sepsis. Sepsis Six. qSOFA. (“The main clinical features of sepsis include hypotension […], tachycardia […], a high (>38.3°C) or low (<36°C) temperature, altered mental status and signs of peripheral shutdown (cool skin, prolonged capillary refill, cyanosis) in severe cases. […] Sepsis is associated with substantial in-hospital morbidity and mortality, and an increased risk of death and re-admission to hospital even if the patient survives until discharge. Prognostic factors in sepsis include patient factors (increasing age, higher comorbidity), site of infection (urosepsis is associated with better outcomes compared to other sources), type of pathogen (nosocomial infections have higher mortality), early administration of antibiotics (which may reduce mortality by 50%) and restoration of perfusion.”)
Acute kidney injury. (“Classically there are three major causative categories of AKI: (i) pre-renal (i.e. hypoperfusion), (ii) renal (i.e. an intrinsic process with the kidneys) and (iii) post-renal (i.e. urinary tract obstruction). The initial evaluation should attempt to determine which of these are leading to AKI in the patient. […] two main complications that arise with AKI [are] volume and electrolyte issues.”)
Acute chest syndrome.
Thrombotic thrombocytopenic purpura. Schistocyte. Plasmapheresis.
Lower gastrointestinal bleeding. WarfarinProthrombin complex concentrate. (“Warfarin is associated with a 1%-3% risk of bleeding each year in patients with atrial fibrillation, and the main risk factors for this include presence of comorbities, interacting medications, poor patient compliance, acute illness and dietary variation in vitamin K intake.”)
Acute back pain. Malignant spinal cord compression (-MSCC). (“Acute back pain is not an uncommon reason for presentation to the Emergency Department […] Although the majority of such presentations represent benign pathology, it is important to exclude more serious pathology such as cord or cauda equina compression, infection or abscess. Features in the history warranting greater concern include a prior history of cancer, recent infection or steroid use, fever, pain in the thoracic region, pain that improves with rest and the presence of urinary symptoms. Similarly, ‘red flag’ examination findings include gait ataxia, generalized weakness, upper motor neurone signs (clonus, hyper-reflexia, extensor plantars), a palpable bladder, saddle anaesthesia and reduced anal tone. […] MSCC affects up to 5% of all cancer patients and is the first manifestation of cancer in a fifth of patients.”)
Neutropenic sepsis. (“Neutropaenic sepsis […] arises as a result of cytotoxic chemotherapy suppressing the bone marrow, leading to depletion of white blood cells and leaving the individual vulnerable to infection. It is one of the most common complications of cancer therapy, carrying a significant mortality rate of ~5%-10%, and should be regarded as a medical emergency. Any patient receiving chemotherapy and presenting with a fever should be assumed to have neutropaenic sepsis until proven otherwise.”)
Bacterial Pneumonia. CURB-65 Pneumonia Severity Score.
Peptic ulcer diseaseUpper gastrointestinal bleeding. Glasgow-Blatchford score. Rockall score.
Generalised tonic-clonic seizure. Status Epilepticus.
“Chest pain is an extremely common presentation in the ED […] Key features that may help point towards particular diagnoses include • Location and radiation – Central chest pain that radiates to the face, neck or arms is classic for MI, whereas the pain may be more posterior (between should blades) in aortic dissection and unilateral in lung disease. • Onset – Sudden or acute onset pain usually indicates a vascular cause (e.g. PE or aortic dissection), whereas cardiac chest pain is typically more subacute in onset and increases over time. • Character – Cardiac pain is usually described as crushing but may often be a gnawing discomfort, whereas pain associated with aortic dissection and gastrointestinal disorders is usually tearing/ripping and burning, respectively. • Exacerbation/alleviation […] myocardial ischaemia will manifest as pain brought on by exercise and relieved by rest, which is a good discriminator between cardiac and non-cardiac pain.”
Syncope. Mobitz type II AV block. (The differential diagnosis for syncope is seizure, and the two may be distinguished by the absence of a quick or spontaneous recovery with a seizure, where a post-ictal state (sleepiness, confusion, lethargy) is present.”)
Atrial Fibrillation. CHADSVASC and HASBLED risk scores. (“AF with rapid ventricular rates is generally managed with control of heart rates through use of beta-blockers or calcium-channel blockers. • Unstable patients with AF may require electrical cardioversion to restore sinus rhythm.”)
Typhoid fever. Dysentery.
Alcohol toxicity. (“Differentials which may mimic acute alcohol intoxication include • Hypoglycemia • Electrolyte disturbance • Vitamin depletion (B12/folate) • Head trauma • Sepsis • Other toxins or drug overdose • Other causes for CNS depression”)
Tricyclic Antidepressant Toxicity. (“Over 50% of suicidal overdoses involve more than one medication and are often taken with alcohol.”)
Suicide. SADPERSONS scale. (“Intentional self-harm results in around 150,000 attendances to the ED [presumably ‘every year’ – US]. These patients are 100 times more likely to commit suicide within the next year compared to the general population. Self-harm and suicide are often used interchangeably, but are in fact two separate entities. Suicide is a self-inflicted intentional act to cause death, whereas self-harm is a complex behaviour to inflict harm but not associated with the thought of dying – a method to relieve mental stress by inflicting physical pain.”)
Cauda equina syndrome (-CES). (“signs and symptoms of lower extremity weakness and pain developing acutely after heavy lifting should raise suspicion for a herniated intervertebral disc, which is the commonest cause of CES. […] CES is a neurosurgical emergency. The goal is to prevent irreversible loss of bowel and bladder function and motor function of the lower extremities. […] A multitude of alternative diagnoses may masquerade as CES – stroke, vascular claudication, deep venous thrombosis, muscle cramps and peripheral neuropathy.”)
Concussion.
Subarachnoid hemorrhage. Arteriovenous malformation.
Ischemic Stroke. AlteplaseMechanical thrombectomy for acute ischemic stroke. (“evaluation and treatment should be based on the understanding that the damage that is done (infarcted brain) is likely to be permanent, and the goal is to prevent further damage (ischaemic brain) and treat reversible causes (secondary prevention). Along those lines, time is critical to the outcome of the patient.”)
Mechanical back pain. Sciatica.
Dislocated shoulder. Bankart lesion. Hill-Sachs lesion. Kocher’s method.
Supracondylar Humerus Fractures. (“Supracondular fractures in the adult are relatively uncommon but are seen in major trauma or in elderly patients where bone quality may be compromised. Elbow fractures need careful neurovascular evaluation […] There are three major nerves that pass through the region: 1. The median nerve […] 2. The radial nerve […] 3. The ulnar nerve […] It is important to assess these three nerves and to document their function individually. The brachial artery passes through the cubital fossa and may be directly injured by bone fragments or suffer intimal damage. […] This is a true orthopaedic and vascular emergency as the upper limb can only tolerate an ischaemia time of around 90 minutes before irreparable damage is sustained.”)
Boxer’s fracture.

May 2, 2018 Posted by | Books, Cancer/oncology, Cardiology, Infectious disease, Medicine, Nephrology, Neurology, Psychiatry, Studies | Leave a comment

A few diabetes papers of interest

i. Economic Costs of Diabetes in the U.S. in 2017.

“This study updates previous estimates of the economic burden of diagnosed diabetes and quantifies the increased health resource use and lost productivity associated with diabetes in 2017. […] The total estimated cost of diagnosed diabetes in 2017 is $327 billion, including $237 billion in direct medical costs and $90 billion in reduced productivity. For the cost categories analyzed, care for people with diagnosed diabetes accounts for 1 in 4 health care dollars in the U.S., and more than half of that expenditure is directly attributable to diabetes. People with diagnosed diabetes incur average medical expenditures of ∼$16,750 per year, of which ∼$9,600 is attributed to diabetes. People with diagnosed diabetes, on average, have medical expenditures ∼2.3 times higher than what expenditures would be in the absence of diabetes. Indirect costs include increased absenteeism ($3.3 billion) and reduced productivity while at work ($26.9 billion) for the employed population, reduced productivity for those not in the labor force ($2.3 billion), inability to work because of disease-related disability ($37.5 billion), and lost productivity due to 277,000 premature deaths attributed to diabetes ($19.9 billion). […] After adjusting for inflation, economic costs of diabetes increased by 26% from 2012 to 2017 due to the increased prevalence of diabetes and the increased cost per person with diabetes. The growth in diabetes prevalence and medical costs is primarily among the population aged 65 years and older, contributing to a growing economic cost to the Medicare program.”

The paper includes a lot of details about how they went about estimating these things, but I decided against including these details here – read the full paper if you’re interested. I did however want to add some additional details, so here goes:

Absenteeism is defined as the number of work days missed due to poor health among employed individuals, and prior research finds that people with diabetes have higher rates of absenteeism than the population without diabetes. Estimates from the literature range from no statistically significant diabetes effect on absenteeism to studies reporting 1–6 extra missed work days (and odds ratios of more absences ranging from 1.5 to 3.3) (1214). Analyzing 2014–2016 NHIS data and using a negative binomial regression to control for overdispersion in self-reported missed work days, we estimate that people with diabetes have statistically higher missed work days—ranging from 1.0 to 4.2 additional days missed per year by demographic group, or 1.7 days on average — after controlling for age-group, sex, race/ethnicity, diagnosed hypertension status (yes/no), and body weight status (normal, overweight, obese, unknown). […] Presenteeism is defined as reduced productivity while at work among employed individuals and is generally measured through worker responses to surveys. Multiple recent studies report that individuals with diabetes display higher rates of presenteeism than their peers without diabetes (12,1517). […] We model productivity loss associated with diabetes-attributed presenteeism using the estimate (6.6%) from the 2012 study—which is toward the lower end of the 1.8–38% range reported in the literature. […] Reduced performance at work […] accounted for 30% of the indirect cost of diabetes.”

It is of note that even with a somewhat conservative estimate of presenteeism, this cost component is an order of magnitude larger than the absenteeism variable. It is worth keeping in mind that this ratio is likely to be different elsewhere; due to the way the American health care system is structured/financed – health insurance is to a significant degree linked to employment – you’d expect the estimated ratio to be different from what you might observe in countries like the UK or Denmark. Some more related numbers from the paper:

Inability to work associated with diabetes is estimated using a conservative approach that focuses on unemployment related to long-term disability. Logistic regression with 2014–2016 NHIS data suggests that people aged 18–65 years with diabetes are significantly less likely to be in the workforce than people without diabetes. […] we use a conservative approach (which likely underestimates the cost associated with inability to work) to estimate the economic burden associated with reduced labor force participation. […] Study results suggest that people with diabetes have a 3.1 percentage point higher rate of being out of the workforce and receiving disability payments compared with their peers without diabetes. The diabetes effect increases with age and varies by demographic — ranging from 2.1 percentage points for non-Hispanic white males aged 60–64 years to 10.6 percentage points for non-Hispanic black females aged 55–59 years.”

“In 2017, an estimated 24.7 million people in the U.S. are diagnosed with diabetes, representing ∼7.6% of the total population (and 9.7% of the adult population). The estimated national cost of diabetes in 2017 is $327 billion, of which $237 billion (73%) represents direct health care expenditures attributed to diabetes and $90 billion (27%) represents lost productivity from work-related absenteeism, reduced productivity at work and at home, unemployment from chronic disability, and premature mortality. Particularly noteworthy is that excess costs associated with medications constitute 43% of the total direct medical burden. This includes nearly $15 billion for insulin, $15.9 billion for other antidiabetes agents, and $71.2 billion in excess use of other prescription medications attributed to higher disease prevalence associated with diabetes. […] A large portion of medical costs associated with diabetes costs is for comorbidities.”

Insulin is ~$15 billion/year, out of a total estimated cost of $327 billion. This is less than 5% of the total cost. Take note of the 70 billion. I know I’ve said this before, but it bears repeating: Most of diabetes-related costs are not related to insulin.

“…of the projected 162 million hospital inpatient days in the U.S. in 2017, an estimated 40.3 million days (24.8%) are incurred by people with diabetes [who make up ~7.6% of the population – see above], of which 22.6 million days are attributed to diabetes. About one-fourth of all nursing/residential facility days are incurred by people with diabetes. About half of all physician office visits, emergency department visits, hospital outpatient visits, and medication prescriptions (excluding insulin and other antidiabetes agents) incurred by people with diabetes are attributed to their diabetes. […] The largest contributors to the cost of diabetes are higher use of prescription medications beyond antihyperglycemic medications ($71.2 billion), higher use of hospital inpatient services ($69.7 billion), medications and supplies to directly treat diabetes ($34.6 billion), and more office visits to physicians and other health providers ($30.0 billion). Approximately 61% of all health care expenditures attributed to diabetes are for health resources used by the population aged ≥65 years […] we estimate the average annual excess expenditures for the population aged <65 years and ≥65 years, respectively, at $6,675 and $13,239. Health care expenditures attributed to diabetes generally increase with age […] The population with diabetes is older and sicker than the population without diabetes, and consequently annual medical expenditures are much higher (on average) than for people without diabetes“.

“Of the estimated 24.7 million people with diagnosed diabetes, analysis of NHIS data suggests that ∼8.1 million are in the workforce. If people with diabetes participated in the labor force at rates similar to their peers without diabetes, there would be ∼2 million additional people aged 18–64 years in the workforce.”

Comparing the 2017 estimates with those produced for 2012, the overall cost of diabetes appears to have increased by ∼25% after adjusting for inflation, reflecting an 11% increase in national prevalence of diagnosed diabetes and a 13% increase in the average annual diabetes-attributed cost per person with diabetes.”

ii. Current Challenges and Opportunities in the Prevention and Management of Diabetic Foot Ulcers.

“Diabetic foot ulcers remain a major health care problem. They are common, result in considerable suffering, frequently recur, and are associated with high mortality, as well as considerable health care costs. While national and international guidance exists, the evidence base for much of routine clinical care is thin. It follows that many aspects of the structure and delivery of care are susceptible to the beliefs and opinion of individuals. It is probable that this contributes to the geographic variation in outcome that has been documented in a number of countries. This article considers these issues in depth and emphasizes the urgent need to improve the design and conduct of clinical trials in this field, as well as to undertake systematic comparison of the results of routine care in different health economies. There is strong suggestive evidence to indicate that appropriate changes in the relevant care pathways can result in a prompt improvement in clinical outcomes.”

“Despite considerable advances made over the last 25 years, diabetic foot ulcers (DFUs) continue to present a very considerable health care burden — one that is widely unappreciated. DFUs are common, the median time to healing without surgery is of the order of 12 weeks, and they are associated with a high risk of limb loss through amputation (14). The 5-year survival following presentation with a new DFU is of the order of only 50–60% and hence worse than that of many common cancers (4,5). While there is evidence that mortality is improving with more widespread use of cardiovascular risk reduction (6), the most recent data — derived from a Veterans Health Adminstration population—reported that 1-, 2-, and 5-year survival was only 81, 69, and 29%, respectively, and the association between mortality and DFU was stronger than that of any macrovascular disease (7). […] There is […] wide variation in clinical outcome within the same country (1315), suggesting that some people are being managed considerably less well than others.”

“Data on community-wide ulcer incidence are very limited. Overall incidences of 5.8 and 6.0% have been reported in selected populations of people with diabetes in the U.S. (2,12,20) while incidences of 2.1 and 2.2% have been reported from less selected populations in Europe—either in all people with diabetes (21) or in those with type 2 disease alone (22). It is not known whether the incidence is changing […] Although a number of risk factors associated with the development of ulceration are well recognized (23), there is no consensus on which dominate, and there are currently no reports of any studies that might justify the adoption of any specific strategy for population selection in primary prevention.”

“The incidence of major amputation is used as a surrogate measure of the failure of DFUs to heal. Its main value lies in the relative ease of data capture, but its value is limited because it is essentially a treatment and not a true measure of disease outcome. In no other major disease (including malignancies, cardiovascular disease, or cerebrovascular disease) is the number of treatments used as a measure of outcome. But despite this and other limitations of major amputation as an outcome measure (36), there is evidence that the overall incidence of major amputation is falling in some countries with nationwide databases (37,38). Perhaps the most convincing data come from the U.K., where the unadjusted incidence has fallen dramatically from about 3.0–3.5 per 1,000 people with diabetes per year in the mid-1990s to 1.0 or less per 1,000 per year in both England and Scotland (14,39).”

New ulceration after healing is high, with ∼40% of people having a new ulcer (whether at the same site or another) within 12 months (10). This is a critical aspect of diabetic foot disease—emphasizing that when an ulcer heals, foot disease must be regarded not as cured, but in remission (10). In this respect, diabetic foot disease is directly analogous to malignancy. It follows that the person whose foot disease is in remission should receive the same structured follow-up as a person who is in remission following treatment for cancer. Of all areas concerned with the management of DFUs, this long-term need for specialist surveillance is arguably the one that should command the greatest attention.

“There is currently little evidence to justify the adoption of very many of the products and procedures currently promoted for use in clinical practice. Guidelines are required to encourage clinicians to adopt only those treatments that have been shown to be effective in robust studies and principally in RCTs. The design and conduct of such RCTs needs improved governance because many are of low standard and do not always provide the evidence that is claimed.”

Incidence numbers like the ones included above will not always give you the full picture when there are a lot of overlapping data points in the sample (due to recurrence), but sometimes that’s all you have. However in the type 1 context we also do have some additional numbers that make it easier to appreciate the scale of the problem in that context. Here are a few additional data from a related publication I blogged some time ago (do keep in mind that estimates are likely to be lower in community samples of type 2 diabetics, even if perhaps nobody actually know precisely how much lower):

“The rate of nontraumatic amputation in T1DM is high, occurring at 0.4–7.2% per year (28). By 65 years of age, the cumulative probability of lower-extremity amputation in a Swedish administrative database was 11% for women with T1DM and 20.7% for men (10). In this Swedish population, the rate of lower-extremity amputation among those with T1DM was nearly 86-fold that of the general population.” (link)

Do keep in mind that people don’t stop getting ulcers once they reach retirement age (the 11%/20.7% is not lifetime risk, it’s a biased lower bound).

iii. Excess Mortality in Patients With Type 1 Diabetes Without Albuminuria — Separating the Contribution of Early and Late Risks.

“The current study investigated whether the risk of mortality in patients with type 1 diabetes without any signs of albuminuria is different than in the general population and matched control subjects without diabetes.”

“Despite significant improvements in management, type 1 diabetes remains associated with an increase in mortality relative to the age- and sex-matched general population (1,2). Acute complications of diabetes may initially account for this increased risk (3,4). However, with increasing duration of disease, the leading contributor to excess mortality is its vascular complications including diabetic kidney disease (DKD) and cardiovascular disease (CVD). Consequently, patients who subsequently remain free of complications may have little or no increased risk of mortality (1,2,5).”

“Mortality was evaluated in a population-based cohort of 10,737 children (aged 0–14 years) with newly diagnosed type 1 diabetes in Finland who were listed on the National Public Health Institute diabetes register, Central Drug Register, and Hospital Discharge Register in 1980–2005 […] We excluded patients with type 2 diabetes and diabetes occurring secondary to other conditions, such as steroid use, Down syndrome, and congenital malformations of the pancreas. […] FinnDiane participants who died were more likely to be male, older, have a longer duration of diabetes, and later age of diabetes onset […]. Notably, none of the conventional variables associated with complications (e.g., HbA1c, hypertension, smoking, lipid levels, or AER) were associated with all-cause mortality in this cohort of patients without albuminuria. […] The most frequent cause of death in the FinnDiane cohort was IHD [ischaemic heart disease, US] […], largely driven by events in patients with long-standing diabetes and/or previously established CVD […]. The mortality rate ratio for IHD was 4.34 (95% CI 2.49–7.57, P < 0.0001). There remained a number of deaths due to acute complications of diabetes, including ketoacidosis and hypoglycemia. This was most significant in patients with a shorter duration of diabetes but still apparent in those with long-standing diabetes[…]. Notably, deaths due to “risk-taking behavior” were lower in adults with type 1 diabetes compared with matched individuals without diabetes: mortality rate ratio was 0.42 (95% CI 0.22–0.79, P = 0.006) […] This was largely driven by the 80% reduction (95% CI 0.06–0.66) in deaths due to alcohol and drugs in males with type 1 diabetes (Table 3). No reduction was observed in female patients (rate ratio 0.90 [95% CI 0.18–4.44]), although the absolute event rate was already more than seven times lower in Finnish women than in men.”

The chief determinant of excess mortality in patients with type 1 diabetes is its complications. In the first 10 years of type 1 diabetes, the acute complications of diabetes dominate and result in excess mortality — more than twice that observed in the age- and sex-matched general population. This early excess explains why registry studies following patients with type 1 diabetes from diagnosis have consistently reported reduced life expectancy, even in patients free of chronic complications of diabetes (68). By contrast, studies of chronic complications, like FinnDiane and the Pittsburgh Epidemiology of Diabetes Complications Study (1,2), have followed participants with, usually, >10 years of type 1 diabetes at baseline. In these patients, the presence or absence of chronic complications of diabetes is critical for survival. In particular, the presence and severity of albuminuria (as a marker of vascular burden) is strongly associated with mortality outcomes in type 1 diabetes (1). […] the FinnDiane normoalbuminuric patients showed increased all-cause mortality compared with the control subjects without diabetes in contrast to when the comparison was made with the Finnish general population, as in our previous publication (1). Two crucial causes behind the excess mortality were acute diabetes complications and IHD. […] Comparisons with the general population, rather than matched control subjects, may overestimate expected mortality, diluting the SMR estimate”.

Despite major improvements in the delivery of diabetes care and other technological advances, acute complications remain a major cause of death both in children and in adults with type 1 diabetes. Indeed, the proportion of deaths due to acute events has not changed significantly over the last 30 years. […] Even in patients with long-standing diabetes (>20 years), the risk of death due to hypoglycemia or ketoacidosis remains a constant companion. […] If it were possible to eliminate all deaths from acute events, the observed mortality rate would have been no different from the general population in the early cohort. […] In long-term diabetes, avoiding chronic complications may be associated with mortality rates comparable with those of the general population; although death from IHD remains increased, this is offset by reduced risk-taking behavior, especially in men.”

“It is well-known that CVD is strongly associated with DKD (15). However, in the current study, mortality from IHD remained higher in adults with type 1 diabetes without albuminuria compared with matched control subjects in both men and women. This is concordant with other recent studies also reporting increased mortality from CVD in patients with type 1 diabetes in the absence of DKD (7,8) and reinforces the need for aggressive cardiovascular risk reduction even in patients without signs of microvascular disease. However, it is important to note that the risk of death from CVD, though significant, is still at least 10-fold lower than observed in patients with albuminuria (1). Alcohol- and drug-related deaths were substantially lower in patients with type 1 diabetes compared with the age-, sex-, and region-matched control subjects. […] This may reflect a selection bias […] Nonparticipation in health studies is associated with poorer health, stress, and lower socioeconomic status (17,18), which are in turn associated with increased risk of premature mortality. It can be speculated that with inclusion of patients with risk-taking behavior, the mortality rate in patients with diabetes would be even higher and, consequently, the SMR would also be significantly higher compared with the general population. Selection of patients who despite long-standing diabetes remained free of albuminuria may also have included individuals more accepting of general health messages and less prone to depression and nihilism arising from treatment failure.”

I think the selection bias problem is likely to be quite significant, as these results don’t really match what I’ve seen in the past. For example a recent Norwegian study on young type 1 diabetics found high mortality in their sample in significant degree due to alcohol-related causes and suicide: “A relatively high proportion of deaths were related to alcohol. […] Death was related to alcohol in 15% of cases. SMR for alcohol-related death was 6.8 (95% CI 4.5–10.3), for cardiovascular death was 7.3 (5.4–10.0), and for violent death was 3.6 (2.3–5.3).” That doesn’t sound very similar to the study above, and that study’s also from Scandinavia. In this study, in which they used data from diabetic organ donors, they found that a large proportion of the diabetics included in the study used illegal drugs: “we observed a high rate of illicit substance abuse: 32% of donors reported or tested positive for illegal substances (excluding marijuana), and multidrug use was common.”

Do keep in mind that one of the main reasons why ‘alcohol-related’ deaths are higher in diabetes is likely to be that ‘drinking while diabetic’ is a lot more risky than is ‘drinking while not diabetic’. On a related note, diabetics may not appreciate the level of risk they’re actually exposed to while drinking, due to community norms etc., so there might be a disconnect between risk preferences and observed behaviour (i.e., a diabetic might be risk averse but still engage in risky behaviours because he doesn’t know how risky those behaviours in which he’s engaging actually are).

Although the illicit drugs study indicates that diabetics at least in some samples are not averse to engaging in risky behaviours, a note of caution is probably warranted in the alcohol context: High mortality from alcohol-mediated acute complications needn’t be an indication that diabetics drink more than non-diabetics; that’s a separate question, you might see numbers like these even if they in general drink less. And a young type 1 diabetic who suffers a cardiac arrhythmia secondary to long-standing nocturnal hypoglycemia and subsequently is found ‘dead in bed’ after a bout of drinking is conceptually very different from a 50-year old alcoholic dying from a variceal bleed or acute pancreatitis. Parenthetically, if it is true that illicit drugs use is common in type 1 diabetics one reason might be that they are aware of the risks associated with alcohol (which is particularly nasty in terms of the metabolic/glycemic consequences in diabetes, compared to some other drugs) and thus they deliberately make a decision to substitute this drug with other drugs less likely to cause acute complications like severe hypoglycemic episodes or DKA (depending on the setting and the specifics, alcohol might be a contributor to both of these complications). If so, classical ‘risk behaviours’ may not always be ‘risk behaviours’ in diabetes. You need to be careful, this stuff’s complicated.

iv. Are All Patients With Type 1 Diabetes Destined for Dialysis if They Live Long Enough? Probably Not.

“Over the past three decades there have been numerous innovations, supported by large outcome trials that have resulted in improved blood glucose and blood pressure control, ultimately reducing cardiovascular (CV) risk and progression to nephropathy in type 1 diabetes (T1D) (1,2). The epidemiological data also support the concept that 25–30% of people with T1D will progress to end-stage renal disease (ESRD). Thus, not everyone develops progressive nephropathy that ultimately requires dialysis or transplantation. This is a result of numerous factors […] Data from two recent studies reported in this issue of Diabetes Care examine the long-term incidence of chronic kidney disease (CKD) in T1D. Costacou and Orchard (7) examined a cohort of 932 people evaluated for 50-year cumulative kidney complication risk in the Pittsburgh Epidemiology of Diabetes Complications study. They used both albuminuria levels and ESRD/transplant data for assessment. By 30 years’ duration of diabetes, ESRD affected 14.5% and by 40 years it affected 26.5% of the group with onset of T1D between 1965 and 1980. For those who developed diabetes between 1950 and 1964, the proportions developing ESRD were substantially higher at 34.6% at 30 years, 48.5% at 40 years, and 61.3% at 50 years. The authors called attention to the fact that ESRD decreased by 45% after 40 years’ duration between these two cohorts, emphasizing the beneficial roles of improved glycemic control and blood pressure control. It should also be noted that at 40 years even in the later cohort (those diagnosed between 1965 and 1980), 57.3% developed >300 mg/day albuminuria (7).”

Numbers like these may seem like ancient history (data from the 60s and 70s), but it’s important to keep in mind that many type 1 diabetics are diagnosed in early childhood, and that they don’t ‘get better’ later on – if they’re still alive, they’re still diabetic. …And very likely macroalbuminuric, at least if they’re from Pittsburgh. I was diagnosed in ’87.

“Gagnum et al. (8), using data from a Norwegian registry, also examined the incidence of CKD development over a 42-year follow-up period in people with childhood-onset (<15 years of age) T1D (8). The data from the Norwegian registry noted that the cumulative incidence of ESRD was 0.7% after 20 years and 5.3% after 40 years of T1D. Moreover, the authors noted the risk of developing ESRD was lower in women than in men and did not identify any difference in risk of ESRD between those diagnosed with diabetes in 1973–1982 and those diagnosed in 1989–2012. They concluded that there is a very low incidence of ESRD among patients with childhood-onset T1D diabetes in Norway, with a lower risk in women than men and among those diagnosed at a younger age. […] Analyses of population-based studies, similar to the Pittsburgh and Norway studies, showed that after 30 years of T1D the cumulative incidences of ESRD were only 10% for those diagnosed with T1D in 1961–1984 and 3% for those diagnosed in 1985–1999 in Japan (11), 3.3% for those diagnosed with T1D in 1977–2007 in Sweden (12), and 7.8% for those diagnosed with T1D in 1965–1999 in Finland (13) (Table 1).”

Do note that ESRD (end stage renal disease) is not the same thing as DKD (diabetic kidney disease), and that e.g. many of the Norwegians who did not develop ESRD nevertheless likely have kidney complications from their diabetes. That 5.3% is not the number of diabetics in that cohort who developed diabetes-related kidney complications, it’s the proportion of them who did and as a result of this needed a new kidney or dialysis in order not to die very soon. Do also keep in mind that both microalbuminuria and macroalbuminuria will substantially increase the risk of cardiovascular disease and -cardiac death. I recall a study where they looked at the various endpoints and found that more diabetics with microalbuminuria eventually died of cardiovascular disease than did ever develop kidney failure – cardiac risk goes up a lot long before end-stage renal disease. ESRD estimates don’t account for the full risk profile, and even if you look at mortality risk the number accounts for perhaps less than half of the total risk attributable to DKD. One thing the ESRD diagnosis does have going for it is that it’s a much more reliable variable indicative of significant pathology than is e.g. microalbuminuria (see e.g. this paper). The paper is short and not at all detailed, but they do briefly discuss/mention these issues:

“…there is a substantive difference between the numbers of people with stage 3 CKD (estimated glomerular filtration rate [eGFR] 30–59 mL/min/1.73 m2) versus those with stages 4 and 5 CKD (eGFR <30 mL/min/1.73 m2): 6.7% of the National Health and Nutrition Examination Survey (NHANES) population compared with 0.1–0.3%, respectively (14). This is primarily because of competing risks, such as death from CV disease that occurs in stage 3 CKD; hence, only the survivors are progressing into stages 4 and 5 CKD. Overall, these studies are very encouraging. Since the 1980s, risk of ESRD has been greatly reduced, while risk of CKD progression persists but at a slower rate. This reduced ESRD rate and slowed CKD progression is largely due to improvements in glycemic and blood pressure control and probably also to the institution of RAAS blockers in more advanced CKD. These data portend even better future outcomes if treatment guidance is followed. […] many medications are effective in blood pressure control, but RAAS blockade should always be a part of any regimen when very high albuminuria is present.”

v. New Understanding of β-Cell Heterogeneity and In Situ Islet Function.

“Insulin-secreting β-cells are heterogeneous in their regulation of hormone release. While long known, recent technological advances and new markers have allowed the identification of novel subpopulations, improving our understanding of the molecular basis for heterogeneity. This includes specific subpopulations with distinct functional characteristics, developmental programs, abilities to proliferate in response to metabolic or developmental cues, and resistance to immune-mediated damage. Importantly, these subpopulations change in disease or aging, including in human disease. […] We will discuss recent findings revealing functional β-cell subpopulations in the intact islet, the underlying basis for these identified subpopulations, and how these subpopulations may influence in situ islet function.”

I won’t cover this one in much detail, but this part was interesting:

“Gap junction (GJ) channels electrically couple β-cells within mouse and human islets (25), serving two main functions. First, GJ channels coordinate oscillatory dynamics in electrical activity and Ca2+ under elevated glucose or GLP-1, allowing pulsatile insulin secretion (26,27). Second, GJ channels lower spontaneous elevations in Ca2+ under low glucose levels (28). GJ coupling is also heterogeneous within the islet (29), leading to some β-cells being highly coupled and others showing negligible coupling. Several studies have examined how electrically heterogeneous cells interact via GJ channels […] This series of experiments indicate a “bistability” in islet function, where a threshold number of poorly responsive β-cells is sufficient to totally suppress islet function. Notably, when islets lacking GJ channels are treated with low levels of the KATP activator diazoxide or the GCK inhibitor mannoheptulose, a subpopulation of cells are silenced, presumably corresponding to the less functional population (30). Only diazoxide/mannoheptulose concentrations capable of silencing >40% of these cells will fully suppress Ca2+ elevations in normal islets. […] this indicates that a threshold number of poorly responsive cells can inhibit the whole islet. Thus, if there exists a threshold number of functionally competent β-cells (∼60–85%), then the islet will show coordinated elevations in Ca2+ and insulin secretion.

Below this threshold number, the islet will lack Ca2+ elevation and insulin secretion (Fig. 2). The precise threshold depends on the characteristics of the excitable and inexcitable populations: small numbers of inexcitable cells will increase the number of functionally competent cells required for islet activity, whereas small numbers of highly excitable cells will do the opposite. However, if GJ coupling is lowered, then inexcitable cells will exert a reduced suppression, also decreasing the threshold required. […] Paracrine communication between β-cells and other endocrine cells is also important for regulating insulin secretion. […] Little is known how these paracrine and juxtacrine mechanisms impact heterogeneous cells.”

vi. Closing in on the Mechanisms of Pulsatile Insulin Secretion.

“Insulin secretion from pancreatic islet β-cells occurs in a pulsatile fashion, with a typical period of ∼5 min. The basis of this pulsatility in mouse islets has been investigated for more than four decades, and the various theories have been described as either qualitative or mathematical models. In many cases the models differ in their mechanisms for rhythmogenesis, as well as other less important details. In this Perspective, we describe two main classes of models: those in which oscillations in the intracellular Ca2+ concentration drive oscillations in metabolism, and those in which intrinsic metabolic oscillations drive oscillations in Ca2+ concentration and electrical activity. We then discuss nine canonical experimental findings that provide key insights into the mechanism of islet oscillations and list the models that can account for each finding. Finally, we describe a new model that integrates features from multiple earlier models and is thus called the Integrated Oscillator Model. In this model, intracellular Ca2+ acts on the glycolytic pathway in the generation of oscillations, and it is thus a hybrid of the two main classes of models. It alone among models proposed to date can explain all nine key experimental findings, and it serves as a good starting point for future studies of pulsatile insulin secretion from human islets.”

This one covers material closely related to the study above, so if you find one of these papers interesting you might want to check out the other one as well. The paper is quite technical but if you were wondering why people are interested in this kind of stuff, one reason is that there’s good evidence at this point that insulin pulsativity is disturbed in type 2 diabetics and so it’d be nice to know why that is so that new drugs can be developed to correct this.

April 25, 2018 Posted by | Biology, Cardiology, Diabetes, Epidemiology, Health Economics, Medicine, Nephrology, Pharmacology, Studies | Leave a comment

100 cases in surgery (II)

Below I have added some links and quotes related to the last half of the book’s coverage.

Ischemic rest pain. (“Rest pain indicates inadequate tissue perfusion. *Urgent investigation and treatment is required to salvage the limb. […] The material of choice for bypass grafting is autogenous vein. […] The long-term patency of prosthetic grafts is inferior compared with autogenous vein.”)
Deep vein thrombosis.
Lymphedema. (“In lymphoedema, the vast majority of patients (>90 per cent) are treated conservatively. […] Debulking operations […] are only considered for a selected few patients where the function of the limb is impaired or those with recurrent attacks of severe cellulitis.”)
Varicose veins. Trendelenburg Test. (“Surgery on the superficial venous system should be avoided in patients with an incompetent deep venous system.”)
Testicular Torsion.
Benign Prostatic Hyperplasia.
Acute pyelonephritis. (“In patients with recurrent infection in the urinary system, significant pathology needs excluding such as malignancy, urinary tract stone disease and abnormal urinary tract anatomy.”)
Renal cell carcinomavon Hippel-Lindau syndrome. (“Approximately one-quarter to one-third of patients with renal cell carcinomas have metastases at presentation. […] The classic presenting triad of loin pain, a mass and haematuria only occurs in about 10 per cent of patients. More commonly, one of these features appears in isolation.”)
Haematuria. (“When taking the history, it is important to elicit the following: •Visible or non-visible: duration of haematuria • Age: cancers are more common with increasing age •Sex: females more likely to have urinary tract infections• Location: during micturition, was the haematuria always present (indicative of renal, ureteric or bladder pathology) or was it only present initially (suggestive of anterior urethral pathology) or present at the end of the stream (posterior urethra, bladder neck)? •Pain: more often associated with infection/inflammation/calculi, whereas malignancy tends to be painless •Associated lower urinary tract symptoms that will be helpful in determining aetiology •History of trauma Travel abroad […] •Previous urological surgery/history/recent instrumentation/prostatic biopsy •Medication, e.g. anticoagulants •Family history •Occupational history, e.g. rubber/dye occupational hazards are risk factors for developing transitional carcinoma of the bladder […] •Smoking status: increased risk, particularly of bladder cancer •General status, e.g. weight loss, reduced appetite […] Anticoagulation can often unmask other pathology in the urinary tract. […] Patients on oral anticoagulation who develop haematuria still require investigation.”)
Urinary retention. (“Acute and chronic retention are usually differentiated by the presence or absence of pain. Acute retention is painful, unlike chronic retention, when the bladder accommodates the increase in volume over time.”)
Colles’ fracture/Distal Radius Fractures. (“In all fractures the distal neurological and vascular status should be assessed.”)
Osteoarthritis. (“Radiological evidence of osteoarthritis is common, with 80 per cent of individuals over 80 years demonstrating some evidence of the condition. […] The commonest symptoms are pain, a reduction in mobility, and deformity of the affected joint.”)
Simmonds’ test.
Patella fracture.
Dislocated shoulder.
Femur fracture. (“Fractured neck of the femur is a relatively common injury following a fall in the elderly population. The rate of hip fracture doubles every decade from the age of 50 years. There is a female preponderance of three to one. […] it is important to take a comprehensive history, concentrating on the mechanism of injury. It is incorrect to assume that all falls are mechanical; it is not uncommon to find that the cause of the fall is actually due to a urinary or chest infection or even a silent myocardial infarction.”)
The Ottawa Ankle Rules.
Septic arthritis.
Carpal tunnel syndrome. Tinel’s test. Phalen’s Test. (“It is important, when examining a patient with suspected carpal tunnel syndrome, to carefully examine their neck, shoulder, and axilla. […] the source of the neurological compression may be proximal to the carpal tunnel”)
Acute Compartment Syndrome. (“Within the limbs there are a number of myofascial compartments. These consist of muscles contained within a relatively fixed-volume structure, bounded by fascial layers and bone. After trauma the pressure in the myofascial compartment increases. This pressure may exceed the venous capillary pressure, resulting in a loss of venous outflow from the compartment. The failure to clear metabolites also leads to the accumulation of fluid as a result of osmosis. If left untreated, the pressure will eventually exceed arterial pressure, leading to significant tissue ischaemia. The damage is irreversible after 4–6 h. Tibial fractures are the commonest cause of an acute compartment syndrome, which is thought to complicate up to 20 per cent of these injuries. […] The classical description of ‘pain out of proportion to the injury’ may [unfortunately] be difficult to determine if the clinician is inexperienced.”)
Hemarthrosis. (“Most knee injuries result in swelling which develops over hours rather than minutes. [A] history of immediate knee swelling suggests that there is a haemarthrosis.”)
Sickle cell crisis.
Cervical Spine Fracture. Neurogenic shock. NEXUS Criteria for C-Spine Imaging.
Slipped Capital Femoral Epiphysis. Trethowan sign. (“At any age, a limp in a child should always be taken seriously.”)

ATLS guidelines. (“The ATLS protocol should be followed even in the presence of obvious limb deformity, to ensure a potentially life-threatening injury is not missed.”)
Peritonsillar Abscess.
Epistaxis. Little’s area.
Croup. Acute epiglottitis. (“Acute epiglottitis is an absolute emergency and is usually caused by Haemophilus influenzae. There is significant swelling, and any attempt to examine the throat may result in airway obstruction. […] In adults it tends to cause a supraglottitis. It has a rapid progression and can lead to total airway obstruction. […] Stridor is an ominous sign and needs to be taken seriously.”)
Bell’s palsy.
Subarachnoid hemorrhageInternational subarachnoid aneurysm trial.
Chronic subdural hematoma. (“This condition is twice as common in men as women. Risk factors include chronic alcoholism, epilepsy, anticoagulant therapy (including aspirin) and thrombocytopenia. CSDH is more common in elderly patients due to cerebral atrophy. […] Initial misdiagnosis is, unfortunately, quite common. […] a chronic subdural haematoma should be suspected in confused patients with a history of a fall.”)
Extradural Haematoma. Cushing response. (“A direct blow to the temporo-parietal area is the commonest cause of an extradural haematoma. The bleed is normally arterial in origin. In 85 per cent of cases there is an associated skull fracture that causes damage to the middle meningeal artery. […] This situation represents a neurosurgical emergency. Without urgent decompression the patient will die. Unlike the chronic subdural, which can be treated with Burr hole drainage, the more dense acute arterial haematoma requires a craniotomy in order to evacuate it.”)
Cauda equina syndromeNeurosurgery for Cauda Equina Syndrome.
ASA classification. (“Patients having an operation within 3 months of a myocardial infarction carry a 30 per cent risk of reinfarction or cardiac death. This drops to 5 per cent after 6 months. […] Patients with COPD have difficulty clearing secretions from the lungs during the postoperative period. They also have a higher risk of basal atelectasis and are more prone to chest infections. These factors in combination with postoperative pain (especially in thoracic or abdominal major surgery) make them prone to respiratory complications. […] Patients with diabetes have an increased risk of postoperative complications because of the presence of microvascular and macrovascular disease: •Atherosclerosis: ischaemic heart disease/peripheral vascular disease/cerebrovascular disease •Nephropathy: renal insufficiency […] •Autonomic neuropathy: gastroparesis, decreased bladder tone •Peripheral neuropathy: lower-extremity ulceration, infection, gangrene •Poor wound healingIncreased risk of infection Tight glycaemic control (6–10 mmol/L) and the prevention of hypoglycaemia are critical in preventing perioperative and postoperative complications. The patient with diabetes should be placed first on the operating list to avoid prolonged fasting.
“)
MalnutritionHartmann’s procedure. (“Malnutrition leads to delayed wound healing, reduced ventilatory capacity, reduced immunity and an increased risk of infection. […] The two main methods of feeding are either by the enteral route or the parenteral route. Enteral feeding is via the gastrointestinal tract. It is less expensive and is associated with fewer complications than feeding by the parenteral route. […] The parenteral route should only be used if there is an inability to ingest, digest, absorb or propulse nutrients through the gastrointestinal tract. It can be administered by either a peripheral or central line. Peripheral parenteral nutrition can cause thrombophlebitis […] Sepsis is the most frequent and serious complication of centrally administered parenteral nutrition.”)
Acute Kidney Injury. (“The aetiology of acute renal failure can be thought of in three main categories: •Pre-renal: the glomerular filtration is reduced because of poor renal perfusion. This is usually caused by hypovolaemia as a result of acute blood loss, fluid depletion or hypotension. […] • Renal: this is the result of damage directly to the glomerulus or tubule. The use of drugs such as NSAIDs, contrast agents or aminoglycosides all have direct nephrotoxic effects. Acute tubular necrosis can occur as a result of prolonged hypoperfusion […]. Pre-existing renal disease such as diabetic nephropathy or glomerulonephritis makes patients more susceptible to further renal injury. •Post-renal: this can be simply the result of a blocked catheter. […] Calculi, blood clots, ureteric ligation and prostatic hypertrophy can also all lead to obstruction of urinary flow.”)
Post-operative ileus.

Pulmonary embolism.

April 18, 2018 Posted by | Books, Cancer/oncology, Cardiology, Gastroenterology, Infectious disease, Medicine, Nephrology, Neurology | Leave a comment

Endocrinology (part 5 – calcium and bone metabolism)

Some observations from chapter 6:

“*Osteoclasts – derived from the monocytic cells; resorb bone. *Osteoblasts – derived from the fibroblast-like cells; make bone. *Osteocytes – buried osteoblasts; sense mechanical strain in bone. […] In order to ensure that bone can undertake its mechanical and metabolic functions, it is in a constant state of turnover […] Bone is laid down rapidly during skeletal growth at puberty. Following this, there is a period of stabilization of bone mass in early adult life. After the age of ~40, there is a gradual loss of bone in both sexes. This occurs at the rate of approximately 0.5% annually. However, in ♀ after the menopause, there is a period of rapid bone loss. The accelerated loss is maximal in the first 2-5 years after the cessation of ovarian function and then gradually declines until the previous gradual rate of loss is once again established. The excess bone loss associated with the menopause is of the order of 10% of skeletal mass. This menopause-associated loss, coupled with higher peak bone mass acquisition in ♂, largely explains why osteoporosis and its associated fractures are more common in ♀.”

“The clinical utility of routine measurements of bone turnover markers is not yet established. […] Skeletal radiology[:] *Useful for: *Diagnosis of fracture. *Diagnosis of specific diseases (e.g. Paget’s disease and osteomalacia). *Identification of bone dysplasia. *Not useful for assessing bone density. […] Isotope bone scans are useful for identifying localized areas of bone disease, such as fracture, metastases, or Paget’s disease. […] Isotope bone scans are particularly useful in Paget’s disease to establish the extent and sites of skeletal involvement and the underlying disease activity. […] Bone biopsy is occasionally necessary for the diagnosis of patients with complex metabolic bone diseases. […] Bone biopsy is not indicated for the routine diagnosis of osteoporosis. It should only be undertaken in highly specialist centres with appropriate expertise. […] Measurement of 24h urinary excretion of calcium provides a measure of risk of renal stone formation or nephrocalcinosis in states of chronic hypercalcaemia. […] 250H vitamin D […] is the main storage form of vitamin D, and the measurement of ‘total vitamin D’ is the most clinically useful measure of vitamin D status. Internationally, there remains controversy around a ‘normal’ or ‘optimal’ concentration of vitamin D. Levels over 50nmol/L are generally accepted as satisfactory and values <25nmol/L representing deficiency. True osteomalacia occurs with vitamin D values <15 nmol/L. Low levels of 250HD can result from a variety of causes […] Bone mass is quoted in terms of the number of standard deviations from an expected mean. […] A reduction of one SD in bone density will approximately double the risk of fracture.”

[I should perhaps add a cautionary note here that while this variable is very useful in general, it is more useful in some contexts than in others; and in some specific disease process contexts it is quite clear that it will tend to underestimate the fracture risk. Type 1 diabetes is a clear example. For more details, see this post.]

“Hypercalcaemia is found in 5% of hospital patients and in 0.5% of the general population. […] Many different disease states can lead to hypercalcaemia. […] In asymptomatic community-dwelling subjects, the vast majority of hypercalcaemia is the result of hyperparathyroidism. […] The clinical features of hypercalcaemia are well recognized […]; unfortunately, they are non-specific […] [They include:] *Polyuria. *Polydipsia. […] *Anorexia. *Vomiting. *Constipation. *Abdominal pain. […] *Confusion. *Lethargy. *Depression. […] Clinical signs of hypercalcaemia are rare. […] the presence of bone pain or fracture and renal stones […] indicate the presence of chronic hypercalcaemia. […] Hypercalcaemia is usually a late manifestation of malignant disease, and the primary lesion is usually evident by the time hypercalcaemia is expressed (50% of patients die within 30 days).”

“Primary hyperparathyroidism [is] [p]resent in up to 1 in 500 of the general population where it is predominantly a disease of post-menopausal ♀ […] The normal physiological response to hypocalcaemia is an increase in PTH secretion. This is termed 2° hyperparathyroidism and is not pathological in as much as the PTH secretion remains under feedback control. Continued stimulation of the parathyroid glands can lead to autonomous production of PTH. This, in turn, causes hypercalcaemia which is termed tertiary hyperparathyroidism. This is usually seen in the context of renal disease […] In majority of patients [with hyperparathyroidism] without end-organ damage, disease is benign and stable. […] Investigation is, therefore, primarily aimed at determining the presence of end-organ damage from hypercalcaemia in order to determine whether operative intervention is indicated. […] It is generally accepted that all patients with symptomatic hyperparathyroidism or evidence of end-organ damage should be considered for parathyroidectomy. This would include: *Definite symptoms of hypercalcaemia. […] *Impaired renal function. *Renal stones […] *Parathyroid bone disease, especially osteitis fibrosis cystica. *Pancreatitis. […] Patients not managed with surgery require regular follow-up. […] <5% fail to become normocalcaemic [after surgery], and these should be considered for a second operation. […] Patients rendered permanently hypoparathyroid by surgery require lifelong supplements of active metabolites of vitamin D with calcium. This can lead to hypercalciuria, and the risk of stone formation may still be present in these patients. […] In hypoparathyroidism, the target serum calcium should be at the low end of the reference range. […] any attempt to raise the plasma calcium well into the normal range is likely to result in unacceptable hypercalciuria”.

“Although hypocalcaemia can result from failure of any of the mechanisms by which serum calcium concentration is maintained, it is usually the result of either failure of PTH secretion or because of the inability to release calcium from bone. […] The clinical features of hypocalcaemia are largely as a result of neuromuscular excitability. In order of  severity, these include: *Tingling – especially of fingers, toes, or lips. *Numbness – especially of fingers, toes, or lips. *Cramps. *Carpopedal spasm. *Stridor due to laryngospasm. *Seizures. […] symptoms of hypocalcaemia tend to reflect the severity and rapidity of onset of the metabolic abnormality. […] there may be clinical signs and symptoms associated with the underlying condition: *Vitamin D deficiency may be associated with generalized bone pain, fractures, or proximal myopathy […] *Hypoparathyroidism can be accompanied by mental slowing and personality disturbances […] *If hypocalcaemia is present during the development of permanent teeth, these may show areas of enamel hypoplasia. This can be a useful physical sign, indicating that the hypocalcaemia is long-standing. […] Acute symptomatic hypocalcaemia is a medical emergency and demands urgent treatment whatever the cause […] *Patients with tetany or seizures require urgent IV treatment with calcium gluconate […] Care must be taken […] as too rapid elevation of the plasma calcium can cause arrhythmias. […] *Treatment of chronic hypocalcaemia is more dependent on the cause. […] In patients with mild parathyroid dysfunction, it may be possible to achieve acceptable calcium concentrations by using calcium supplements alone. […] The majority of patients will not achieve adequate control with such treatment. In those cases, it is necessary to use vitamin D or its metabolites in pharmacological doses to maintain plasma calcium.”

“Pseudohypoparathyroidism[:] *Resistance to parathyroid hormone action. *Due to defective signalling of PTH action via cell membrane receptor. *Also affects TSH, LH, FSH, and GH signalling. […] Patients with the most common type of pseudohypoparathyroidism (type 1a) have a characteristic set of skeletal abnormalities, known as Albright’s hereditary osteodystrophy. This comprises: *Short stature. *Obesity. *Round face. *Short metacarpals. […] The principles underlying the treatment of pseudohypoparathyroidism are the same as those underlying hypoparathyroidism. *Patients with the most common form of pseudohypoparathyroidism may have resistance to the action of other hormones which rely on G protein signalling. They, therefore, need to be assessed for thyroid and gonadal dysfunction (because of defective TSH and gonadotrophin action). If these deficiencies are present, they need to be treated in the conventional manner.”

“Osteomalacia occurs when there is inadequate mineralization of mature bone. Rickets is a disorder of the growing skeleton where there is inadequate mineralization of bone as it is laid down at the epiphysis. In most instances, osteomalacia leads to build-up of excessive unmineralized osteoid within the skeleton. In rickets, there is build-up of unmineralized osteoid in the growth plate. […] These two related conditions may coexist. […] Clinical features [of osteomalacia:] *Bone pain. *Deformity. *Fracture. *Proximal myopathy. *Hypocalcaemia (in vitamin D deficiency). […] The majority of patients with osteomalacia will show no specific radiological abnormalities. *The most characteristic abnormality is the Looser’s zone or pseudofracture. If these are present, they are virtually pathognomonic of osteomalacia. […] Oncogenic osteomalacia[:] Certain tumours appear to be able to produce FGF23 which is phosphaturic. This is rare […] Clinically, such patients usually present with profound myopathy as well as bone pain and fracture. […] Complete removal of the tumour results in resolution of the biochemical and skeletal abnormalities. If this is not possible […], treatment with vitamin D metabolites and phosphate supplements […] may help the skeletal symptoms.”

Hypophosphataemia[:] Phosphate is important for normal mineralization of bone. In the absence of sufficient phosphate, osteomalacia results. […] In addition, phosphate is important in its own right for neuromuscular function, and profound hypophosphataemia can be accompanied by encephalopathy, muscle weakness, and cardiomyopathy. It must be remembered that, as phosphate is primarily an intracellular anion, a low plasma phosphate does not necessarily represent actual phosphate depletion. […] Mainstay [of treatment] is phosphate replacement […] *Long-term administration of phosphate supplements stimulates parathyroid activity. This can lead to hypercalcaemia, a further fall in phosphate, with worsening of the bone disease […] To minimize parathyroid stimulation, it is usual to give one of the active metabolites of vitamin D in conjunction with phosphate.”

“Although the term osteoporosis refers to the reduction in the amount of bony tissue within the skeleton, this is generally associated with a loss of structural integrity of the internal architecture of the bone. The combination of both these changes means that osteoporotic bone is at high risk of fracture, even after trivial injury. […] Historically, there has been a primary reliance on bone mineral density as a threshold for treatment, whereas currently there is far greater emphasis on assessing individual patients’ risk of fracture that incorporates multiple clinical risk factors as well as bone mineral density. […] Osteoporosis may arise from a failure of the body to lay down sufficient bone during growth and maturation; an earlier than usual onset of bone loss following maturity; or an rate of that loss. […] Early menopause or late puberty (in ♂ or ♀) is associated with risk of osteoporosis. […] Lifestyle factors affecting bone mass [include:] *weight-bearing exercise [increase bone mass] […] *Smoking. *Excessive alcohol. *Nulliparity. *Poor calcium nutrition. [These all decrease bone mass] […] The risk of osteoporotic fracture increases with age. Fracture rates in ♂ are approximately half of those seen in ♀ of the same age. An ♀ aged 50 has approximately a 1:2 chance [risk, surely… – US] of sustaining an osteoporotic fracture in the rest of her life. The corresponding figure for a ♂ is 1:5. […] One-fifth of hip fracture victims will die within 6 months of the injury, and only 50% will return to their previous level of independence.”

“Any fracture, other than those affecting fingers, toes, or face, which is caused by a fall from standing height or less is called a fragility (low-trauma) fracture, and underlying osteoporosis should be considered. Patients suffering such a fracture should be considered for investigation and/or treatment for osteoporosis. […] [Osteoporosis is] [u]sually clinically silent until an acute fracture. *Two-thirds of vertebral fractures do not come to clinical attention. […] Osteoporotic vertebral fractures only rarely lead to neurological impairment. Any evidence of spinal cord compression should prompt a search for malignancy or other underlying cause. […] Osteoporosis does not cause generalized skeletal pain. […] Biochemical markers of bone turnover may be helpful in the calculation of fracture risk and in judging the response to drug therapies, but they have no role in the diagnosis of osteoporosis. […] An underlying cause for osteoporosis is present in approximately 10-30% of women and up to 50% of men with osteoporosis. […] 2° causes of osteoporosis are more common in ♂ and need to be excluded in all ♂ with osteoporotic fracture. […] Glucocorticoid treatment is one of the major 2° causes of osteoporosis.”

February 22, 2018 Posted by | Books, Cancer/oncology, Diabetes, Epidemiology, Medicine, Nephrology, Neurology, Pharmacology | Leave a comment

Endocrinology (part 3 – adrenal glands)

Some observations from chapter 3 below.

“The normal adrenal gland weigh 4-5g. The cortex represents 90% of the normal gland and surrounds the medulla. […] Glucocorticoid (cortisol […]) production occurs from the zona fasciculata, and adrenal androgens arise from the zona reticularis. Both of these are under the control of ACTH [see also my previous post about the book – US], which regulates both steroid synthesis and also adrenocortical growth. […] Mineralocorticoid (aldosterone […]) synthesis occurs in zona glomerulosa, predominantly under the control of the renin-angiotensin system […], although ACTH also contributes to its regulation. […] The adrenal gland […] also produces sex steroids in the form of dehydroepiandrostenedione (DHEA) and androstenedione. The synthetic pathway is under the control of ACTH. Urinary steroid profiling provides quantitative information on the biosynthetic and catabolic pathways. […] CT is the most widely used modality for imaging the adrenal glands. […] MRI can also reliably detect adrenal masses >5-10mm in diameter and, in some circumstances, provides additional information to CT […] PET can be useful in locating tumours and metastases. […] Adrenal vein sampling (AVS) […] can be useful to lateralize an adenoma or to differentiate an adenoma from bilateral hyperplasia. […] AVS is of particular value in lateralizing small aldosterone-producing adenomas that cannot easily be visualized on CT or MRI. […] The procedure should only be undertaken in patients in whom surgery is feasible and desired […] [and] should be carried out in specialist centres only; centres with <20 procedures per year have been shown to have poor success rates”.

“The majority of cases of mineralocorticoid excess are due to excess aldosterone production, […] typically associated with hypertension and hypokalemia. *Primary hyperaldosteronism is a disorder of autonomous aldosterone hypersecretion with suppressed renin levels. *Secondary hyperaldosteronism occurs when aldosterone hypersecretion occurs 2° [secondary, US] to elevated circulating renin levels. This is typical of heart failure, cirrhosis, or nephrotic syndrome but can also be due to renal artery stenosis and, occasionally, a very rare renin-producing tumour (reninoma). […] Primary hyperaldosteronism is present in around 10% of hypertensive patients. It is the most prevalent form of secondary hypertension. […] Aldosterone causes renal sodium retention and potassium loss. This results in expansion of body sodium content, leading to suppression of renal renin synthesis. The direct action of aldosterone on the distal nephron causes sodium retention and loss and hydrogen and potassium ions, resulting in a hypokalaemic alkalosis, although serum potassium […] may be normal in up to 50% of cases. Aldosterone has pathophysiological effects on a range of other tissues, causing cardiac fibrosis, vascular endothelial dysfunction, and nephrosclerosis. […] hypertension […] is often resistant to conventional therapy. […] Hypokalaemia is usually asymptomatic. […] Occasionally, the clinical syndrome of hyperaldosteronism is not associated with excess aldosterone. […] These conditions are rare.”

“Bilateral adrenal hyperplasia [make up] 60% [of cases of primary hyperaldosteronism]. […] Conn’s syndrome (aldosterone-producing adrenal adenoma) [make up] 35%. […] The pathophysiology of bilateral adrenal hyperplasia is not understood, and it is possible that it represents an extreme end of the spectrum of low renin essential hypertension. […] Aldosterone-producing carcinoma[s] [are] [r]are and usually associated with excessive secretion of other corticosteroids (cortisol, androgen, oestrogen). […] Indications [for screening include:] *Patients resistant to conventional antihypertensive medication (i.e. not controlled on three agents). *Hypertension associated with hypokalaemia […] *Hypertension developing before age of 40 years. […] Confirmation of autonomous aldosterone production is made by demonstrating failure to suppress aldosterone in face of sodium/volume loading. […] A number of tests have been described that are said to differentiate between the various subtypes of 1° [primary, US] aldosteronism […]. However, none of these are sufficiently specific to influence management decisions”.

“Laparoscopic adrenalectomy is the treatment of choice for aldosterone-secreting adenomas […] and laparoscopic adrenalectomy […] has become the procedure of choice for removal of most adrenal tumours. *Hypertension is cured in about 70%. *If it persists […], it is more amenable to medical treatment. *Overall, 50% become normotensive in 1 month and 70% within 1 year. […] Medical therapy remains an option for patients with bilateral disease and those with a solitary adrenal adenoma who are unlikely to be cured by surgery, who are unfit for operation, or who express a preference for medical management. *The mineralocorticoid receptor antagonist spironolactone […] has been used successfully for many years to treat hypertension and hypokalaemia associated with bilateral adrenal hyperplasia […] Side effects are common – particularly gynaecomastia and impotence in ♂, menstrual irregularities in ♀, and GI effects. […] Eplerenone […] is a mineralocorticoid receptor antagonist without antiandrogen effects and hence greater selectivity and less side effects than spironolactone. *Alternative drugs include the potassium-sparing diuretics amiloride and triamterene.”

“Cushing’s syndrome results from chronic excess cortisol [see also my second post in this series] […] The causes may be classified as ACTH-dependent and ACTH-independent. […] ACTH-independent Cushing’s syndrome […] is due to adrenal tumours (benign and malignant), and is responsible for 10-15% of cases of Cushing’s syndrome. […] Benign adrenocortical adenomas (ACA) are usually encapsulated and <4cm in diameter. They are usually associated with pure glucocorticoid excess. *Adrenocortical carcinomas (ACC) are usually >6cm in diameter, […] and are not infrequently associated with local invasion and metastases at the time of diagnosis. Adrenal carcinomas are characteristically associated with the excess secretion of several hormones; most frequently found is the combination of cortisol and androgen (precursors) […] ACTH-dependent Cushing’s results in bilateral adrenal hyperplasia, thus one has to firmly differentiate between ACTH-dependent and independent causes of Cushing’s before assuming bilateral adrenal hyperplasia as the primary cause of disease. […] It is important to note that, in patients with adrenal carcinoma, there may also be features related to excessive androgen production in ♀ and also a relatively more rapid time course of development of the syndrome. […] Patients with ACTH-independent Cushing’s syndrome do not suppress cortisol […] on high-dose dexamethasone testing and fail to show a rise in cortisol and ACTH following administration of CRH. […] ACTH-independent causes are adrenal in origin, and the mainstay of further investigation is adrenal imaging by CT”.

“Adrenal adenomas, which are successfully treated with surgery, have a good prognosis, and recurrence is unlikely. […] Bilateral adrenalectomy [in the context of bilateral adrenal hyperplasia] is curative. Lifelong glucocorticoid and mineralocorticoid treatment is [however] required. […] The prognosis for adrenal carcinoma is very poor despite surgery. Reports suggest a 5-year survival of 22% and median survival time of 14 months […] Treatment of adrenocortical carcinoma (ACC) should be carried out in a specialist centre, with expert surgeons, oncologists, and endocrinologists with extensive treatment in treating ACC. This improves survival.”

“Adrenal insufficiency [AI, US] is defined by the lack of cortisol, i.e. glucocorticoid deficiency, may be due to destruction of the adrenal cortex (1°, Addison’s disease and congenital adrenal hyperplasia (CAH) […] or due to disordered pituitary and hypothalamic function (2°). […] *Permanent adrenal insufficiency is found in 5 in 10,000 population. *The most frequent cause is hypothalamic-pituitary damage, which is the cause of AI in 60% of affected patients. *The remaining 40% of cases are due to primary failure of the adrenal to synthesize cortisol, almost equal prevalence of Addison’s disease (mostly of autoimmune origin, prevalence 0.9-1.4 in 10,000) and congenital adrenal hyperplasia (0.7-1.0 in 10,000). *2° adrenal insufficiency due to suppression of pituitary-hypothalamic function by exogenously administered, supraphysiological glucocorticoid doses for treatment of, for example, COPD or rheumatoid arthritis, is much more common (50-200 in 10,000 population). However, adrenal function in these patients can recover”.

“[In primary AI] [a]drenal gland destruction or dysfunction occurs due to a disease process which usually involves all three zones of the adrenal cortex, resulting in inadequate glucocorticoid, mineralocorticoid, and adrenal androgen precursor secretion. The manifestations of insufficiency do not usually appear until at least 90% of the gland has been destroyed and are usually gradual in onset […] Acute adrenal insufficiency may occur in the context of acute septicaemia […] Mineralocorticoid deficiency leads to reduced sodium retention and hyponatraemia and hypotension […] Androgen deficiency presents in ♀ with reduced axillary and pubic hair and reduced libido. (Testicular production of androgens is more important in ♂). [In secondary AI] [i]nadequate ACTH results in deficient cortisol production (and ↓ androgens in ♀). […] Mineralocorticoid secretion remains normal […] The onset is usually gradual, with partial ACTH deficiency resulting in reduced response to stress. […] Lack of stimulation of skin MC1R due to ACTH deficiency results in pale skin appearance. […] [In 1° adrenal insufficiency] hyponatraemia is present in 90% and hyperkalaemia in 65%. […] Undetectable serum cortisol is diagnostic […], but the basal cortisol is often in the normal range. A cortisol >550nmol/L precludes the diagnosis. At times of acute stress, an inappropriately low cortisol is very suggestive of the diagnosis.”

“Autoimmune adrenalitis[:] Clinical features[:] *Anorexia and weight loss (>90%). *Tiredness. *Weakness – generalized, no particular muscle groups. […] Dizziness and postural hypotension. *GI symptoms – nausea and vomiting, abdominal pain, diarrhea. *Arthralgia and myalgia. […] *Mediated by humoral and cell-mediated immune mechanisms. Autoimmune insufficiency associated with polyglandular autoimmune syndrome is more common in ♀ (70%). *Adrenal cortex antibodies are present in the majority of patients at diagnosis, and […] they are still found in approximately 70% of patients 10 years later. Up to 20% patients/year with [positive] antibodies develop adrenal insufficiency. […] *Antiadrenal antibodies are found in <2% of patients with other autoimmune endocrine disease (Hashimoto’s thyroiditis, diabetes mellitus, autoimmune hypothyroidism, hypoparathyroidism, pernicious anemia). […] antibodies to other endocrine glands are commonly found in patients with autoimmune adrenal insufficiency […] However, the presence of antibodies does not predict subsequent manifestation of organ-specific autoimmunity. […] Patients with type 1 diabetes mellitus and autoimmune thyroid disease only rarely develop autoimmune adrenal insufficiency. Approximately 60% of patients with Addison’s disease have other autoimmune or endocrine disorders. […] The adrenals are small and atrophic in chronic autoimmune adrenalitis.”

“Autoimmune polyglandular syndrome (APS) type 1[:] *Also known as autoimmune polyendocrinopathy, candidiasis, and ectodermal dystrophy (APECED). […] [C]hildhood onset. *Chronic mucocutaneous candidiasis. *Hypoparathyroidism (90%), 1° adrenal insufficiency (60%). *1° gonadal failure (41%) – usually after Addison’s diagnosis. *1° hypothyroidism. *Rarely hypopituitarism, diabetes insipidus, type 1 diabetes mellitus. […] APS type 2[:] *Adult onset. *Adrenal insufficiency (100%). 1° autoimmune thyroid disease (70%) […] Type 1 diabetes mellitus (5-20%) – often before Addison’s diagnosis. *1° gonadal failure in affected women (5-20%). […] Schmidt’s syndrome: *Addison’s disease, and *Autoimmune hypothyroidism. *Carpenter syndrome: *Addison’s disease, and *Autoimmune hypothyroidism, and/or *Type 1 diabetes mellitus.”

“An adrenal incidentaloma is an adrenal mass that is discovered incidentally upon imaging […] carried out for reasons other than a suspected adrenal pathology.  […] *Autopsy studies suggest incidence prevalence of adrenal masses of 1-6% in the general population. *Imagining studies suggest that adrenal masses are present 2-3% in the general population. Incidence increases with ageing, and 8-10% of 70-year olds harbour an adrenal mass. […] It is important to determine whether the incidentally discovered adrenal mass is: *Malignant. *Functioning and associated with excess hormonal secretion.”

January 17, 2018 Posted by | Books, Cancer/oncology, Diabetes, Epidemiology, Immunology, Medicine, Nephrology, Pharmacology | Leave a comment

Endocrinology (part 2 – pituitary)

Below I have added some observations from the second chapter of the book, which covers the pituitary gland.

“The pituitary gland is centrally located at the base of the brain in the sella turcica within the sphenoid bone. It is attached to the hypothalamus by the pituitary stalk and a fine vascular network. […] The pituitary measures around 13mm transversely, 9mm anteroposteriorly, and 6mm vertically and weighs approximately 100mg. It increases during pregnancy to almost twice its normal size, and it decreases in the elderly. *Magnetic resonance imaging (MRI) currently provides the optimal imaging of the pituitary gland. *Computed tomography (CT) scans may still be useful in demonstrating calcification in tumours […] and hyperostosis in association with meningiomas or evidence of bone destruction. […] T1– weighted images demonstrate cerebrospinal fluid (CSF) as dark grey and brain as much whiter. This imagining is useful for demonstrating anatomy clearly. […] On T1– weighted images, pituitary adenomas are of lower signal intensity than the remainder of the normal gland. […] The presence of microadenomas may be difficult to demonstrate.”

“Hypopituitarism refers to either partial or complete deficiency of anterior and/or posterior pituitary hormones and may be due to [primary] pituitary disease or to hypothalamic pathology which interferes with the hypothalamic control of the pituitary. Causes: *Pituitary tumours. *Parapituitary tumours […] *Radiotherapy […] *Pituitary infarction (apoplexy), Sheehan’s syndrome. *Infiltration of the pituitary gland […] *infection […] *Trauma […] *Subarachnoid haemorrhage. *Isolated hypothalamic-releasing hormone deficiency, e.g. Kallmann’s syndrome […] *Genetic causes [Let’s stop here: Point is, lots of things can cause pituitary problems…] […] The clinical features depend on the type and degree of hormonal deficits, and the rate of its development, in addition to whether there is intercurrent illness. In the majority of cases, the development of hypopituitarism follows a characteristic order, which secretion of GH [growth hormone, US], then gonadotrophins being affected first, followed by TSH [Thyroid-Stimulating Hormone, US] and ACTH [Adrenocorticotropic Hormone, US] secretion at a later stage. PRL [prolactin, US] deficiency is rare, except in Sheehan’s syndrome associated with failure of lactation. ADH [antidiuretic hormone, US] deficiency is virtually unheard of with pituitary adenomas but may be seen rarely with infiltrative disorders and trauma. The majority of the clinical features are similar to those occurring when there is target gland insufficiency. […] NB Houssay phenomenon. Amelioration of diabetes mellitus in patients with hypopituitarism due to reduction in counter-regulatory hormones. […] The aims of investigation of hypopituitarism are to biochemically assess the extent of pituitary hormone deficiency and also to elucidate the cause. […] Treatment involves adequate and appropriate hormone replacement […] and management of the underlying cause.”

“Apoplexy refers to infarction of the pituitary gland due to either haemorrhage or ischaemia. It occurs most commonly in patients with pituitary adenomas, usually macroadenomas […] It is a medical emergency, and rapid hydrocortisone replacement can be lifesaving. It may present with […] sudden onset headache, vomiting, meningism, visual disturbance, and cranial nerve palsy.”

“Anterior pituitary hormone replacement therapy is usually performed by replacing the target hormone rather than the pituitary or hypothalamic hormone that is actually deficient. The exceptions to this are GH replacement […] and when fertility is desired […] [In the context of thyroid hormone replacement:] In contrast to replacement in [primary] hypothyroidism, the measurement of TSH cannot be used to assess adequacy of replacment in TSH deficiency due to hypothalamo-pituitary disease. Therefore, monitoring of treatment in order to avoid under- and over-replacement should be via both clinical assessment and by measuring free thyroid hormone concentrations […] [In the context of sex hormone replacement:] Oestrogen/testosterone administration is the usual method of replacement, but gonadotrophin therapy is required if fertility is desired […] Patients with ACTH deficiency usually need glucocorticoid replacement only and do not require mineralcorticoids, in contrast to patients with Addison’s disease. […] Monitoring of replacement [is] important to avoid over-replacement which is associated with BP, elevated glucose and insulin, and reduced bone mineral density (BMD). Under-replacement leads to the non-specific symptoms, as seen in Addison’s disease […] Conventional replacement […] may overtreat patients with partial ACTH deficiency.”

“There is now a considerable amount of evidence that there are significant and specific consequences of GH deficiency (GDH) in adults and that many of these features improve with GH replacement therapy. […] It is important to differentiate between adult and childhood onset GDH. […] the commonest cause in childhood is an isolated variable deficiency of GH-releasing hormone (GHRH) which may resolve in adult life […] It is, therefore, important to retest patients with childhood onset GHD when linear growth is completed (50% recovery of this group). Adult onset. GHD usually occurs [secondarily] to a structural pituitary or parapituitary condition or due to the effects of surgical treatment or radiotherapy. Prevalence[:] *Adult onset GHD 1/10,000 *Adult GHD due to adult and childhood onset GHD 3/10,000. Benefits of GH replacement[:] *Improved QoL and psychological well-being. *Improved exercise capacity. *↑ lean body mass and reduced fat mass. *Prolonged GH replacement therapy (>12-24 months) has been shown to increase BMD, which would be expected to reduce fracture rate. *There are, as yet, no outcome studies in terms of cardiovascular mortality. However, GH replacement does lead to a reduction (~15%) in cholesterol. GH replacement also leads to improved ventricular function and ↑ left ventricular mass. […] All patients with GHD should be considered for GH replacement therapy. […] adverse effects experienced with GH replacement usually resolve with dose reduction […] GH treatment may be associated with impairment of insulin sensitivity, and therefore markers of glycemia should be monitored. […] Contraindications to GH replacement[:] *Active malignancy. *Benign intracranial hypertension. *Pre-proliferative/proliferative retinopathy in diabetes mellitus.”

“*Pituitary adenomas are the most common pituitary disease in adults and constitute 10-15% of primary brain tumours. […] *The incidence of clinically apparent pituitary disease is 1 in 10,000. *Pituitary carcinoma is very rare (<0.1% of all tumours) and is most commonly ACTH- or prolactin-secreting. […] *Microadenoma <1cm. *Macroadenoma >1cm. [In terms of the functional status of tumours, the break-down is as follows:] *Prolactinoma 35-40%. *Non-functioning 30-35%. Growth hormone (acromegaly) 10-15%. *ACTH adenoma (Cushing’s disease) 5-10% *TSH adenoma <5%. […] Pituitary disease is associated with an increased mortality, predominantly due to vascular disease. This may be due to oversecretion of GH or ACTH, hormone deficiencies or excessive replacement (e.g. of hydrocortisone).”

“*Prolactinomas are the commonest functioning pituitary tumour. […] Malignant prolactinomas are very rare […] [Clinical features of hyperprolactinaemia:] *Galactorrhoea (up to 90%♀, <10% ♂). *Disturbed gonadal function [menstrual disturbance, infertility, reduced libido, ED in ♂] […] Hyperprolactinaemia is associated with a long-term risk of BMD. […] Hypothyroidism and chronic renal failure are causes of hyperprolactinaemia. […] Antipsychotic agents are the most likely psychotrophic agents to cause hyperprolactinaemia. […] Macroadenomas are space-occupying tumours, often associated with bony erosion and/or cavernous sinus invasion. […] *Invasion of the cavernous sinus may lead to cranial nerve palsies. *Occasionally, very invasive tumours may erode bone and present with a CSF leak or [secondary] meningitis. […] Although microprolactinomas may expand in size without treatment, the vast majority do not. […] Macroprolactinomas, however, will continue to expand and lead to pressure effects. Definite treatment of the tumour is, therefore, necessary.”

“Dopamine agonist treatment […] leads to suppression of PRL in most patients [with prolactinoma], with [secondary] effects of normalization of gonadal function and termination of galactorrhoea. Tumour shrinkage occurs at a variable rate (from 24h to 6-12 months) and extent and must be carefully monitored. Continued shrinkage may occur for years. Slow chiasmal decompression will correct visual field defects in the majority of patients, and immediate surgical decompression is not necessary. […] Cabergoline is more effective in normalization of PRL in microprolactinoma […], with fewer side effects than bromocriptine. […] Tumour enlargement following initial shrinkage on treatment is usually due to non-compliance. […] Since the introduction of dopamine agonist treatment, transsphenoidal surgery is indicated only for patients who are resistant to, or intolerant of, dopamine agonist treatment. The cure rate for macroprolactinomas treated with surgery is poor (30%), and, therefore, drug treatment is first-line in tumours of all size. […] Standard pituitary irradiation leads to slow reduction (over years) of PRL in the majority of patients. […] Radiotherapy is not indicated in the management of patients with microprolactinomas. It is useful in the treatment of macroprolactinomas once the tumour has been shrunken away from the chiasm, only if the tumour is resistant.”

“Acromegaly is the clinical condition resulting from prolonged excessive GH and hence IGF-1 secretion in adults. GH secretion is characterized by blunting of pulsatile secretion and failure of GH to become undetectable during the 24h day, unlike normal controls. […] *Prevalence 40-86 cases/million population. Annual incidence of new cases in the UK is 4/million population. *Onset is insidious, and there is, therefore, often a considerable delay between onset of clinical features and diagnosis. Most cases are diagnosed at 40-60 years. […] Pituitary gigantism [is] [t]he clinical syndrome resulting from excess GH secretion in children prior to fusion of the epiphyses. […] growth velocity without premature pubertal manifestations should arouse suspicion of pituitary gigantism. […] Causes of acromegaly[:] *Pituitary adenoma (>99% of cases). Macroadenomas 60-80%, microadenomas 20-40%. […] The clinical features arise from the effects of excess GH/IGF-1, excess PRL in some (as there is co-secretion of PRL in a minority (30%) of tumours […] and the tumour mass. [Signs and symptoms:] * sweating -> 80% of patients. *Headaches […] *Tiredness and lethargy. *Joint pains. *Change in ring or shoe size. *Facial appearance. Coarse features […] enlarged nose […] prognathism […] interdental separation. […] Enlargement of hands and feet […] [Complications:] *Hypertension (40%). *Insulin resistance and impaired glucose tolerance (40%)/diabetes mellitus (20%). *Obstructive sleep apnea – due to soft tissue swelling […] Ischaemic heart disease and cerebrovascular disease.”

“Management of acromegaly[:] The management strategy depends on the individual patient and also on the tumour size. Lowering of GH is essential in all situations […] Transsphenoidal surgery […] is usually the first line for treatment in most centres. *Reported cure rates vary: 40-91% for microadenomas and 10-48% for macroadenomas, depending on surgical expertise. […] Using the definition of post-operative cure as mean GH <2.5 micrograms/L, the reported recurrence rate is low (6% at 5 years). Radiotherapy […] is usually reserved for patients following unsuccessful transsphenoidal surgery, only occasionally is it used as [primary] therapy. […] normalization of mean GH may take several years and, during this time, adjunctive medical treatment (usually with somatostatin analogues) is required. […] Radiotherapy can induce GH deficiency which may need GH therapy. […] Somatostatin analogues lead to suppresion of GH secretion in 20-60% of patients with acromegaly. […] some patients are partial responders, and although somatostatin analogues will lead to lowering of mean GH, they do not suppress to normal despite dose escalation. These drugs may be used as [primary] therapy where the tumour does not cause mass effects or in patients who have received surgery and/or radiotherapy who have elevated mean GH. […] Dopamine agonists […] lead to lowering of GH levels but, very rarely, lead to normalization of GH or IGF-1 (<30%). They may be helpful, particularly if there is coexistent secretion of PRL, and, in these cases, there may be significant tumour shrinkage. […] GH receptor antagonists [are] [i]ndicated for somatostatin non-responders.”

“Cushing’s syndrome is an illness resulting from excess cortisol secretion, which has a high mortality if left untreated. There are several causes of hypercortisolaemia which must be differentiated, and the commonest cause is iatrogenic (oral, inhaled, or topical steroids). […] ACTH-dependent Cushing’s must be differentiated from ACTH-independent disease (usually due to an adrenal adenoma, or, rarely, carcinoma […]). Once a diagnosis of ACTH-dependent disease has been established, it is important to differentiate between pituitary-dependent (Cushing’s disease) and ectopic secretion. […] [Cushing’s disease is rare;] annual incidence approximately 2/million. The vast majority of Cushing’s syndrome is due to a pituitary ACTH-secreting corticotroph microadenoma. […] The features of Cushing’s syndrome are progressive and may be present for several years prior to diagnosis. […] *Facial appearance – round plethoric complexion, acne and hirsutism, thinning of scalp hair. *Weight gain – truncal obesity, buffalo hump […] *Skin – thin and fragile […] easy bruising […] *Proximal muscle weakness. *Mood disturbance – labile, depression, insomnia, psychosis. *Menstrual disturbance. *Low libido and impotence. […] Associated features [include:] *Hypertension (>50%) due to mineralocorticoid effects of cortisol […] *Impaired glucose tolerance/diabetes mellitus (30%). *Osteopenia and osteoporosis […] *Vascular disease […] *Susceptibility to infections. […] Cushing’s is associated with a hypercoagulable state, with increased cardiovascular thrombotic risks. […] Hypercortisolism suppresses the thyroidal, gonadal, and GH axes, leading to lowered levels of TSH and thyroid hormones as well as reduced gonadotrophins, gonadal steroids, and GH.”

“Treatment of Cushing’s disease[:] Transsphenoidal surgery [is] the first-line option in most cases. […] Pituitary radiotherapy [is] usually administered as second-line treatment, following unsuccessful transsphenoidal surgery. […] Medical treatment [is] indicated during the preoperative preparation of patients or while awaiting radiotherapy to be effective or if surgery or radiotherapy are contraindicated. *Inhibitors of steroidogenesis: metyrapone is usually used first-line, but ketoconazole should be used as first-line in children […] Disadvantage of these agents inhibiting steroidogenesis is the need to increase the dose to maintain control, as ACTH secretion will increase as cortisol concentrations decrease. […] Successful treatment (surgery or radiotherapy) of Cushing’s disease leads to cortisol deficiency and, therefore, glucocorticoid replacement therapy is essential. […] *Untreated [Cushing’s] disease leads to an approximately 30-50% mortality at 5 years, owing to vascular disease and susceptibility to infections. *Treated Cushing’s syndrome has a good prognosis […] *Although the physical features and severe psychological disorders associated with Cushing’s improve or resolve within weeks or months of successful treatment, more subtle mood disturbance may persist for longer. Adults may also have impaired cognitive function. […] it is likely that there is an cardiovascular risk. *Osteoporosis will usually resolve in children but may not improve significantly in older patients. […] *Hypertension has been shown to resolve in 80% and diabetes mellitus in up to 70%. *Recent data suggests that mortality even with successful treatment of Cushing’s is increased significantly.”

“The term incidentaloma refers to an incidentally detected lesion that is unassociated with hormonal hyper- or hyposecretion and has a benign natural history. The increasingly frequent detection of these lesions with technological improvements and more widespread use of sophisticated imaging has led to a management challenge – which, if any, lesions need investigation and/or treatment, and what is the optimal follow-up strategy (if required at all)? […] *Imaging studies using MRI demonstrate pituitary microadenomas in approximately 10% of normal volunteers. […] Clinically significant pituitary tumours are present in about 1 in 1,000 patients. […] Incidentally detected microadenomas are very unlikely (<10%) to increase in size whereas larger incidentally detected meso- and macroadenomas are more likely (40-50%) to enlarge. Thus, conservative management in selected patients may be appropriate for microadenomas which are incidentally detected […]. Macroadenomas should be treated, if possible.”

“Non-functioning pituitary tumours […] are unassociated with clinical syndromes of anterior pituitary hormone excess. […] Non-functioning pituitary tumours (NFA) are the commonest pituitary macroadenoma. They represent around 28% of all pituitary tumours. […] 50% enlarge, if left untreated, at 5 years. […] Tumour behaviour is variable, with some tumours behaving in a very indolent, slow-growing manner and others invading the sphenoid and cavernous sinus. […] At diagnosis, approximately 50% of patients are gonadotrophin-deficient. […] The initial definitive management in virtually every case is surgical. This removes mass effects and may lead to some recovery of pituitary function in around 10%. […] The use of post-operative radiotherapy remains controversial. […] The regrowth rate at 10 years without radiotherapy approaches 45% […] administration of post-operative radiotherapy reduces this regrowth rate to <10%. […] however, there are sequelae to radiotherapy – with a significant long-term risk of hypopituitarism and a possible risk of visual deterioration and malignancy in the field of radiation. […] Unlike the case for GH- and PRL-secreting tumours, medical therapy for NFAs is usually unhelpful […] Gonadotrophinomas […] are tumours that arise from the gonadotroph cells of the pituitary gland and produce FSH, LH, or the α subunit. […] they are usually silent and unassociated with excess detectable secretion of LH and FSH […] [they] present in the same manner as other non-functioning pituitary tumours, with mass effects and hypopituitarism […] These tumours are managed as non-functioning tumours.”

“The posterior lobe of the pituitary gland arises from the forebrain and comprises up to 25% of the normal adult pituitary gland. It produces arginine vasopressin and oxytocin. […] Oxytoxin has no known role in ♂ […] In ♀, oxytoxin contracts the pregnant uterus and also causes breast duct smooth muscle contraction, leading to breast milk ejection during breastfeeding. […] However, oxytoxin deficiency has no known adverse effect on parturition or breastfeeding. […] Arginine vasopressin is the major determinant of renal water excretion and, therefore, fluid balance. It’s main action is to reduce free water clearance. […] Many substances modulate vasopressin secretion, including the catecholamines and opioids. *The main site of action of vasopressin is in the collecting duct and the thick ascending loop of Henle […] Diabetes Insipidus (DI) […] is defined as the passage of large volumes (>3L/24h) of dilute urine (osmolality <300mOsm/kg). [It may be] [d]ue to deficiency of circulating arginine vasopressin [or] [d]ue to renal resistance to vasopressin.” […lots of other causes as well – trauma, tumours, inflammation, infection, vascular, drugs, genetic conditions…]

Hyponatraemia […] Incidence *1-6% of hospital admissions Na<130mmol/L. *15-22% hospital admissions Na<135mmol/L. […] True clinically apparent hyponatraemia is associated with either excess water or salt deficiency. […] Features *Depend on the underlying cause and also on the rate of development of hyponatraemia. May develop once sodium reaches 115mmol/L or earlier if the fall is rapid. Level at 100mmol/L or less is life-threatening. *Features of excess water are mainly neurological because of brain injury […] They include confusion and headache, progressing to seizures and coma. […] SIADH [Syndrome of Inappropriate ADH, US] is a common cause of hyponatraemia. […] The elderly are more prone to SIADH, as they are unable to suppress ADH as efficiently […] ↑ risk of hyponatraemia with SSRIs. […] rapid overcorrection of hyponatraemia may cause central pontine myelinolysis (demyelination).”

“The hypothalamus releases hormones that act as releasing hormones at the anterior pituitary gland. […] The commonest syndrome to be associated with the hypothalamus is abnormal GnRH secretion, leading to reduced gonadotrophin secretion and hypogonadism. Common causes are stress, weight loss, and excessive exercise.”

January 14, 2018 Posted by | Books, Cancer/oncology, Cardiology, Diabetes, Epidemiology, Medicine, Nephrology, Neurology, Ophthalmology, Pharmacology | Leave a comment

A few diabetes papers of interest

i. Type 2 Diabetes in the Real World: The Elusive Nature of Glycemic Control.

“Despite U.S. Food and Drug Administration (FDA) approval of over 40 new treatment options for type 2 diabetes since 2005, the latest data from the National Health and Nutrition Examination Survey show that the proportion of patients achieving glycated hemoglobin (HbA1c) <7.0% (<53 mmol/mol) remains around 50%, with a negligible decline between the periods 2003–2006 and 2011–2014. The Healthcare Effectiveness Data and Information Set reports even more alarming rates, with only about 40% and 30% of patients achieving HbA1c <7.0% (<53 mmol/mol) in the commercially insured (HMO) and Medicaid populations, respectively, again with virtually no change over the past decade. A recent retrospective cohort study using a large U.S. claims database explored why clinical outcomes are not keeping pace with the availability of new treatment options. The study found that HbA1c reductions fell far short of those reported in randomized clinical trials (RCTs), with poor medication adherence emerging as the key driver behind the disconnect. In this Perspective, we examine the implications of these findings in conjunction with other data to highlight the discrepancy between RCT findings and the real world, all pointing toward the underrealized promise of FDA-approved therapies and the critical importance of medication adherence. While poor medication adherence is not a new issue, it has yet to be effectively addressed in clinical practice — often, we suspect, because it goes unrecognized. To support the busy health care professional, innovative approaches are sorely needed.”

“To better understand the differences between usual care and clinical trial HbA1c results, multivariate regression analysis assessed the relative contributions of key biobehavioral factors, including baseline patient characteristics, drug therapy, and medication adherence (21). Significantly, the key driver was poor medication adherence, accounting for 75% of the gap […]. Adherence was defined […] as the filling of one’s diabetes prescription often enough to cover ≥80% of the time one was recommended to be taking the medication (34). By this metric, proportion of days covered (PDC) ≥80%, only 29% of patients were adherent to GLP-1 RA treatment and 37% to DPP-4 inhibitor treatment. […] These data are consistent with previous real-world studies, which have demonstrated that poor medication adherence to both oral and injectable antidiabetes agents is very common (3537). For example, a retrospective analysis [of] adults initiating oral agents in the DPP-4 inhibitor (n = 61,399), sulfonylurea (n = 134,961), and thiazolidinedione (n = 42,012) classes found that adherence rates, as measured by PDC ≥80% at the 1-year mark after the initial prescription, were below 50% for all three classes, at 47.3%, 41.2%, and 36.7%, respectively (36). Rates dropped even lower at the 2-year follow-up (36)”

“Our current ability to assess adherence and persistence is based primarily on review of pharmacy records, which may underestimate the extent of the problem. For example, using the definition of adherence of the Centers for Medicare & Medicaid Services — PDC ≥80% — a patient could miss up to 20% of days covered and still be considered adherent. In retrospective studies of persistence, the permissible gap after the last expected refill date often extends up to 90 days (39,40). Thus, a patient may have a gap of up to 90 days and still be considered persistent.

Additionally, one must also consider the issue of primary nonadherence; adherence and persistence studies typically only include patients who have completed a first refill. A recent study of e-prescription data among 75,589 insured patients found that nearly one-third of new e-prescriptions for diabetes medications were never filled (41). Finally, none of these measures take into account if the patient is actually ingesting or injecting the medication after acquiring his or her refills.”

“Acknowledging and addressing the problem of poor medication adherence is pivotal because of the well-documented dire consequences: a greater likelihood of long-term complications, more frequent hospitalizations, higher health care costs, and elevated mortality rates (4245). In patients younger than 65, hospitalization risk in one study (n = 137,277) was found to be 30% at the lowest level of adherence to antidiabetes medications (1–19%) versus 13% at the highest adherence quintile (80–100%) […]. In patients over 65, a separate study (n = 123,235) found that all-cause hospitalization risk was 37.4% in adherent cohorts (PDC ≥80%) versus 56.2% in poorly adherent cohorts (PDC <20%) (45). […] Furthermore, for every 1,000 patients who increased adherence to their antidiabetes medications by just 1%, the total medical cost savings was estimated to be $65,464 over 3 years (45). […] “for reasons that are still unclear, the N.A. [North American] patient groups tend to have lower compliance and adherence compared to global rates during large cardiovascular studies” (46,47).”

“There are many potential contributors to poor medication adherence, including depressive affect, negative treatment perceptions, lack of patient-physician trust, complexity of the medication regimen, tolerability, and cost (48). […] A recent review of interventions addressing problematic medication adherence in type 2 diabetes found that few strategies have been shown consistently to have a marked positive impact, particularly with respect to HbA1c lowering, and no single intervention was identified that could be applied successfully to all patients with type 2 diabetes (53). Additional evidence indicates that improvements resulting from the few effective interventions, such as pharmacy-based counseling or nurse-managed home telemonitoring, often wane once the programs end (54,55). We suspect that the efficacy of behavioral interventions to address medication adherence will continue to be limited until there are more focused efforts to address three common and often unappreciated patient obstacles. First, taking diabetes medications is a burdensome and often difficult activity for many of our patients. Rather than just encouraging patients to do a better job of tolerating this burden, more work is needed to make the process easier and more convenient. […] Second, poor medication adherence often represents underlying attitudinal problems that may not be a strictly behavioral issue. Specifically, negative beliefs about prescribed medications are pervasive among patients, and behavioral interventions cannot be effective unless these beliefs are addressed directly (35). […] Third, the issue of access to medications remains a primary concern. A study by Kurlander et al. (51) found that patients selectively forgo medications because of cost; however, noncost factors, such as beliefs, satisfaction with medication-related information, and depression, are also influential.”

ii. Diabetes Research and Care Through the Ages. An overview article which might be of interest especially to people who’re not much familiar with the history of diabetes research and -treatment (a topic which is also very nicely covered in Tattersall’s book). Despite including a historical review of various topics, it also includes many observations about e.g. current (and future?) practice. Some random quotes:

“Arnoldo Cantani established a new strict level of treatment (9). He isolated his patients “under lock and key, and allowed them absolutely no food but lean meat and various fats. In the less severe cases, eggs, liver, and shell-fish were permitted. For drink the patients received water, plain or carbonated, and dilute alcohol for those accustomed to liquors, the total fluid intake being limited to one and one-half to two and one-half liters per day” (6).

Bernhard Naunyn encouraged a strict carbohydrate-free diet (6,10). He locked patients in their rooms for 5 months when necessary for “sugar-freedom” (6).” […let’s just say that treatment options have changed slightly over time – US]

“The characteristics of insulin preparations include the purity of the preparation, the concentration of insulin, the species of origin, and the time course of action (onset, peak, duration) (25). From the 1930s to the early 1950s, one of the major efforts made was to develop an insulin with extended action […]. Most preparations contained 40 (U-40) or 80 (U-80) units of insulin per mL, with U-10 and U-20 eliminated in the early 1940s. U-100 was introduced in 1973 and was meant to be a standard concentration, although U-500 had been available since the early 1950s for special circumstances. Preparations were either of mixed beef and pork origin, pure beef, or pure pork. There were progressive improvements in the purity of preparations as chemical techniques improved. Prior to 1972, conventional preparations contained 8% noninsulin proteins. […] In the early 1980s, “human” insulins were introduced (26). These were made either by recombinant DNA technology in bacteria (Escherichia coli) or yeast (Saccharomyces cerevisiae) or by enzymatic conversion of pork insulin to human insulin, since pork differed by only one amino acid from human insulin. The powerful nature of recombinant DNA technology also led to the development of insulin analogs designed for specific effects. These include rapid-acting insulin analogs and basal insulin analogs.”

“Until 1996, the only oral medications available were biguanides and sulfonylureas. Since that time, there has been an explosion of new classes of oral and parenteral preparations. […] The management of type 2 diabetes (T2D) has undergone rapid change with the introduction of several new classes of glucose-lowering therapies. […] the treatment guidelines are generally clear in the context of using metformin as the first oral medication for T2D and present a menu approach with respect to the second and third glucose-lowering medication (3032). In order to facilitate this decision, the guidelines list the characteristics of each medication including side effects and cost, and the health care provider is expected to make a choice that would be most suited for patient comorbidities and health care circumstances. This can be confusing and contributes to the clinical inertia characteristic of the usual management of T2D (33).”

“Perhaps the most frustrating barrier to optimizing diabetes management is the frequent occurrence of clinical inertia (whenever the health care provider does not initiate or intensify therapy appropriately and in a timely fashion when therapeutic goals are not reached). More broadly, the failure to advance therapy in an appropriate manner can be traced to physician behaviors, patient factors, or elements of the health care system. […] Despite clear evidence from multiple studies, health care providers fail to fully appreciate that T2D is a progressive disease. T2D is associated with ongoing β-cell failure and, as a consequence, we can safely predict that for the majority of patients, glycemic control will deteriorate with time despite metformin therapy (35). Continued observation and reinforcement of the current therapeutic regimen is not likely to be effective. As an example of real-life clinical inertia for patients with T2D on monotherapy metformin and an HbA1c of 7 to <8%, it took on the average 19 months before additional glucose-lowering therapy was introduced (36). The fear of hypoglycemia and weight gain are appropriate concerns for both patient and physician, but with newer therapies these undesirable effects are significantly diminished. In addition, health care providers must appreciate that achieving early and sustained glycemic control has been demonstrated to have long-term benefits […]. Clinicians have been schooled in the notion of a stepwise approach to therapy and are reluctant to initiate combination therapy early in the course of T2D, even if the combination intervention is formulated as a fixed-dose combination. […] monotherapy metformin failure rates with a starting HbA1c >7% are ∼20% per year (35). […] To summarize the current status of T2D at this time, it should be clearly emphasized that, first and foremost, T2D is characterized by a progressive deterioration of glycemic control. A stepwise medication introduction approach results in clinical inertia and frequently fails to meet long-term treatment goals. Early/initial combination therapies that are not associated with hypoglycemia and/or weight gain have been shown to be safe and effective. The added value of reducing CV outcomes with some of these newer medications should elevate them to a more prominent place in the treatment paradigm.”

iii. Use of Adjuvant Pharmacotherapy in Type 1 Diabetes: International Comparison of 49,996 Individuals in the Prospective Diabetes Follow-up and T1D Exchange Registries.

“The majority of those with type 1 diabetes (T1D) have suboptimal glycemic control (14); therefore, use of adjunctive pharmacotherapy to improve control has been of clinical interest. While noninsulin medications approved for type 2 diabetes have been reported in T1D research and clinical practice (5), little is known about their frequency of use. The T1D Exchange (T1DX) registry in the U.S. and the Prospective Diabetes Follow-up (DPV) registry in Germany and Austria are two large consortia of diabetes centers; thus, they provide a rich data set to address this question.

For the analysis, 49,996 pediatric and adult patients with diabetes duration ≥1 year and a registry update from 1 April 2015 to 1 July 2016 were included (19,298 individuals from 73 T1DX sites and 30,698 individuals from 354 DPV sites). Adjuvant medication use (metformin, glucagon-like peptide 1 [GLP-1] receptor agonists, dipeptidyl peptidase 4 [DPP-4] inhibitors, sodium–glucose cotransporter 2 [SGLT2] inhibitors, and other noninsulin diabetes medications including pramlintide) was extracted from participant medical records. […] Adjunctive agents, whose proposed benefits may include the ability to improve glycemic control, reduce insulin doses, promote weight loss, and suppress dysregulated postprandial glucagon secretion, have had little penetrance as part of the daily medical regimen of those in the registries studied. […] The use of any adjuvant medication was 5.4% in T1DX and 1.6% in DPV (P < 0.001). Metformin was the most commonly reported medication in both registries, with 3.5% in the T1DX and 1.3% in the DPV (P < 0.001). […] Use of adjuvant medication was associated with older age, higher BMI, and longer diabetes duration in both registries […] it is important to note that registry data did not capture the intent of adjuvant medications, which may have been to treat polycystic ovarian syndrome in women […here’s a relevant link, US].”

iv. Prevalence of and Risk Factors for Diabetic Peripheral Neuropathy in Youth With Type 1 and Type 2 Diabetes: SEARCH for Diabetes in Youth Study. I recently covered a closely related paper here (paper # 2) but the two papers cover different data sets so I decided it would be worth including this one in this post anyway. Some quotes:

“We previously reported results from a small pilot study comparing the prevalence of DPN in a subset of youth enrolled in the SEARCH for Diabetes in Youth (SEARCH) study and found that 8.5% of 329 youth with T1D (mean ± SD age 15.7 ± 4.3 years and diabetes duration 6.2 ± 0.9 years) and 25.7% of 70 youth with T2D (age 21.6 ± 4.1 years and diabetes duration 7.6 ± 1.8 years) had evidence of DPN (9). […this is the paper I previously covered here, US] Recently, we also reported the prevalence of microvascular and macrovascular complications in youth with T1D and T2D in the entire SEARCH cohort (10).

In the current study, we examined the cross-sectional and longitudinal risk factors for DPN. The aims were 1) to estimate prevalence of DPN in youth with T1D and T2D, overall and by age and diabetes duration, and 2) to identify risk factors (cross-sectional and longitudinal) associated with the presence of DPN in a multiethnic cohort of youth with diabetes enrolled in the SEARCH study.”

“The SEARCH Cohort Study enrolled 2,777 individuals. For this analysis, we excluded participants aged <10 years (n = 134), those with no antibody measures for etiological definition of diabetes (n = 440), and those with incomplete neuropathy assessment […] (n = 213), which reduced the analysis sample size to 1,992 […] There were 1,734 youth with T1D and 258 youth with T2D who participated in the SEARCH study and had complete data for the variables of interest. […] Seven percent of the participants with T1D and 22% of those with T2D had evidence of DPN.”

“Among youth with T1D, those with DPN were older (21 vs. 18 years, P < 0.0001), had a longer duration of diabetes (8.7 vs. 7.8 years, P < 0.0001), and had higher DBP (71 vs. 69 mmHg, P = 0.02), BMI (26 vs. 24 kg/m2, P < 0.001), and LDL-c levels (101 vs. 96 mg/dL, P = 0.01); higher triglycerides (85 vs. 74 mg/dL, P = 0.005); and lower HDL-c levels (51 vs. 55 mg/dL, P = 0.01) compared to those without DPN. The prevalence of DPN was 5% among nonsmokers vs. 10% among the current and former smokers (P = 0.001). […] Among youth with T2D, those with DPN were older (23 vs. 22 years, P = 0.01), had longer duration of diabetes (8.6 vs. 7.6 years; P = 0.002), and had lower HDL-c (40 vs. 43 mg/dL, P = 0.04) compared with those without DPN. The prevalence of DPN was higher among males than among females: 30% of males had DPN compared with 18% of females (P = 0.02). The prevalence of DPN was twofold higher in current smokers (33%) compared with nonsmokers (15%) and former smokers (17%) (P = 0.01). […] [T]he prevalence of DPN was further assessed by 5-year increment of diabetes duration in individuals with T1D or T2D […]. There was an approximately twofold increase in the prevalence of DPN with an increase in duration of diabetes from 5–10 years to >10 years for both the T1D group (5–13%) (P < 0.0001) and the T2D group (19–36%) (P = 0.02). […] in an unadjusted logistic regression model, youth with T2D were four times more likely to develop DPN compared with those with T1D, and though this association was attenuated, it remained significant independent of age, sex, height, and glycemic control (OR 2.99 [1.91; 4.67], P < 0.001)”.

“The prevalence estimates for DPN found in our study for youth with T2D are similar to those in the Australian cohort (8) but lower for youth with T1D than those reported in the Danish (7) and Australian (8) cohorts. The nationwide Danish Study Group for Diabetes in Childhood reported a prevalence of 62% among 339 adolescents and youth with T1D (age 12–27 years, duration 9–25 years, and HbA1c 9.7 ± 1.7%) using the vibration perception threshold to assess DPN (7). The higher prevalence in this cohort compared with ours (62 vs. 7%) could be due to the longer duration of diabetes (9–25 vs. 5–13 years) and reliance on a single measure of neuropathy (vibration perception threshold) as opposed to our use of the MNSI, which includes vibration as well as other indicators of neuropathy. In the Australian study, Eppens et al. (8) reported abnormalities in peripheral nerve function in 27% of the 1,433 adolescents with T1D (median age 15.7 years, median diabetes duration 6.8 years, and mean HbA1c 8.5%) and 21% of the 68 adolescents with T2D (median age 15.3 years, median diabetes duration 1.3 years, and mean HbA1c 7.3%) based on thermal and vibration perception threshold. These data are thus reminiscent of the persistent inconsistencies in the definition of DPN, which are reflected in the wide range of prevalence estimates being reported.”

“The alarming rise in rates of DPN for every 5-year increase in duration, coupled with poor glycemic control and dyslipidemia, in this cohort reinforces the need for clinicians rendering care to youth with diabetes to be vigilant in screening for DPN and identifying any risk factors that could potentially be modified to alter the course of the disease (2830). The modifiable risk factors that could be targeted in this young population include better glycemic control, treatment of dyslipidemia, and smoking cessation (29,30) […]. The sharp increase in rates of DPN over time is a reminder that DPN is one of the complications of diabetes that must be a part of the routine annual screening for youth with diabetes.”

v. Diabetes and Hypertension: A Position Statement by the American Diabetes Association.

“Hypertension is common among patients with diabetes, with the prevalence depending on type and duration of diabetes, age, sex, race/ethnicity, BMI, history of glycemic control, and the presence of kidney disease, among other factors (13). Furthermore, hypertension is a strong risk factor for atherosclerotic cardiovascular disease (ASCVD), heart failure, and microvascular complications. ASCVD — defined as acute coronary syndrome, myocardial infarction (MI), angina, coronary or other arterial revascularization, stroke, transient ischemic attack, or peripheral arterial disease presumed to be of atherosclerotic origin — is the leading cause of morbidity and mortality for individuals with diabetes and is the largest contributor to the direct and indirect costs of diabetes. Numerous studies have shown that antihypertensive therapy reduces ASCVD events, heart failure, and microvascular complications in people with diabetes (48). Large benefits are seen when multiple risk factors are addressed simultaneously (9). There is evidence that ASCVD morbidity and mortality have decreased for people with diabetes since 1990 (10,11) likely due in large part to improvements in blood pressure control (1214). This Position Statement is intended to update the assessment and treatment of hypertension among people with diabetes, including advances in care since the American Diabetes Association (ADA) last published a Position Statement on this topic in 2003 (3).”

“Hypertension is defined as a sustained blood pressure ≥140/90 mmHg. This definition is based on unambiguous data that levels above this threshold are strongly associated with ASCVD, death, disability, and microvascular complications (1,2,2427) and that antihypertensive treatment in populations with baseline blood pressure above this range reduces the risk of ASCVD events (46,28,29). The “sustained” aspect of the hypertension definition is important, as blood pressure has considerable normal variation. The criteria for diagnosing hypertension should be differentiated from blood pressure treatment targets.

Hypertension diagnosis and management can be complicated by two common conditions: masked hypertension and white-coat hypertension. Masked hypertension is defined as a normal blood pressure in the clinic or office (<140/90 mmHg) but an elevated home blood pressure of ≥135/85 mmHg (30); the lower home blood pressure threshold is based on outcome studies (31) demonstrating that lower home blood pressures correspond to higher office-based measurements. White-coat hypertension is elevated office blood pressure (≥140/90 mmHg) and normal (untreated) home blood pressure (<135/85 mmHg) (32). Identifying these conditions with home blood pressure monitoring can help prevent overtreatment of people with white-coat hypertension who are not at elevated risk of ASCVD and, in the case of masked hypertension, allow proper use of medications to reduce side effects during periods of normal pressure (33,34).”

“Diabetic autonomic neuropathy or volume depletion can cause orthostatic hypotension (35), which may be further exacerbated by antihypertensive medications. The definition of orthostatic hypotension is a decrease in systolic blood pressure of 20 mmHg or a decrease in diastolic blood pressure of 10 mmHg within 3 min of standing when compared with blood pressure from the sitting or supine position (36). Orthostatic hypotension is common in people with type 2 diabetes and hypertension and is associated with an increased risk of mortality and heart failure (37).

It is important to assess for symptoms of orthostatic hypotension to individualize blood pressure goals, select the most appropriate antihypertensive agents, and minimize adverse effects of antihypertensive therapy.”

“Taken together, […] meta-analyses consistently show that treating patients with baseline blood pressure ≥140 mmHg to targets <140 mmHg is beneficial, while more intensive targets may offer additional though probably less robust benefits. […] Overall, compared with people without diabetes, the relative benefits of antihypertensive treatment are similar, and absolute benefits may be greater (5,8,40). […] Multiple-drug therapy is often required to achieve blood pressure targets, particularly in the setting of diabetic kidney disease. However, the use of both ACE inhibitors and ARBs in combination is not recommended given the lack of added ASCVD benefit and increased rate of adverse events — namely, hyperkalemia, syncope, and acute kidney injury (7173). Titration of and/or addition of further blood pressure medications should be made in a timely fashion to overcome clinical inertia in achieving blood pressure targets. […] there is an absence of high-quality data available to guide blood pressure targets in type 1 diabetes. […] Of note, diastolic blood pressure, as opposed to systolic blood pressure, is a key variable predicting cardiovascular outcomes in people under age 50 years without diabetes and may be prioritized in younger adults (46,47). Though convincing data are lacking, younger adults with type 1 diabetes might more easily achieve intensive blood pressure levels and may derive substantial long-term benefit from tight blood pressure control.”

“Lifestyle management is an important component of hypertension treatment because it lowers blood pressure, enhances the effectiveness of some antihypertensive medications, promotes other aspects of metabolic and vascular health, and generally leads to few adverse effects. […] Lifestyle therapy consists of reducing excess body weight through caloric restriction, restricting sodium intake (<2,300 mg/day), increasing consumption of fruits and vegetables […] and low-fat dairy products […], avoiding excessive alcohol consumption […] (53), smoking cessation, reducing sedentary time (54), and increasing physical activity levels (55). These lifestyle strategies may also positively affect glycemic and lipid control and should be encouraged in those with even mildly elevated blood pressure.”

“Initial treatment for hypertension should include drug classes demonstrated to reduce cardiovascular events in patients with diabetes: ACE inhibitors (65,66), angiotensin receptor blockers (ARBs) (65,66), thiazide-like diuretics (67), or dihydropyridine CCBs (68). For patients with albuminuria (urine albumin-to-creatinine ratio [UACR] ≥30 mg/g creatinine), initial treatment should include an ACE inhibitor or ARB in order to reduce the risk of progressive kidney disease […]. In the absence of albuminuria, risk of progressive kidney disease is low, and ACE inhibitors and ARBs have not been found to afford superior cardioprotection when compared with other antihypertensive agents (69). β-Blockers may be used for the treatment of coronary disease or heart failure but have not been shown to reduce mortality as blood pressure–lowering agents in the absence of these conditions (5,70).”

vi. High Illicit Drug Abuse and Suicide in Organ Donors With Type 1 Diabetes.

“Organ donors with type 1 diabetes represent a unique population for research. Through a combination of immunological, metabolic, and physiological analyses, researchers utilizing such tissues seek to understand the etiopathogenic events that result in this disorder. The Network for Pancreatic Organ Donors with Diabetes (nPOD) program collects, processes, and distributes pancreata and disease-relevant tissues to investigators throughout the world for this purpose (1). Information is also available, through medical records of organ donors, related to causes of death and psychological factors, including drug use and suicide, that impact life with type 1 diabetes.

We reviewed the terminal hospitalization records for the first 100 organ donors with type 1 diabetes in the nPOD database, noting cause, circumstance, and mechanism of death; laboratory results; and history of illicit drug use. Donors were 45% female and 79% Caucasian. Mean age at time of death was 28 years (range 4–61) with mean disease duration of 16 years (range 0.25–52).”

“Documented suicide was found in 8% of the donors, with an average age at death of 21 years and average diabetes duration of 9 years. […] Similarly, a type 1 diabetes registry from the U.K. found that 6% of subjects’ deaths were attributed to suicide (2). […] Additionally, we observed a high rate of illicit substance abuse: 32% of donors reported or tested positive for illegal substances (excluding marijuana), and multidrug use was common. Cocaine was the most frequently abused substance. Alcohol use was reported in 35% of subjects, with marijuana use in 27%. By comparison, 16% of deaths in the U.K. study were deemed related to drug misuse (2).”

“We fully recognize the implicit biases of an organ donor–based population, which may not be […’may not be’ – well, I guess that’s one way to put it! – US] directly comparable to the general population. Nevertheless, the high rate of suicide and drug use should continue to spur our energy and resources toward caring for the emotional and psychological needs of those living with type 1 diabetes. The burden of type 1 diabetes extends far beyond checking blood glucose and administering insulin.”

January 10, 2018 Posted by | Cardiology, Diabetes, Epidemiology, Medicine, Nephrology, Neurology, Pharmacology, Psychiatry, Studies | Leave a comment

A few diabetes papers of interest

i. Mechanisms and Management of Diabetic Painful Distal Symmetrical Polyneuropathy.

“Although a number of the diabetic neuropathies may result in painful symptomatology, this review focuses on the most common: chronic sensorimotor distal symmetrical polyneuropathy (DSPN). It is estimated that 15–20% of diabetic patients may have painful DSPN, but not all of these will require therapy. […] Although the exact pathophysiological processes that result in diabetic neuropathic pain remain enigmatic, both peripheral and central mechanisms have been implicated, and extend from altered channel function in peripheral nerve through enhanced spinal processing and changes in many higher centers. A number of pharmacological agents have proven efficacy in painful DSPN, but all are prone to side effects, and none impact the underlying pathophysiological abnormalities because they are only symptomatic therapy. The two first-line therapies approved by regulatory authorities for painful neuropathy are duloxetine and pregabalin. […] All patients with DSPN are at increased risk of foot ulceration and require foot care, education, and if possible, regular podiatry assessment.”

“The neuropathies are the most common long-term microvascular complications of diabetes and affect those with both type 1 and type 2 diabetes, with up to 50% of older type 2 diabetic patients having evidence of a distal neuropathy (1). These neuropathies are characterized by a progressive loss of nerve fibers affecting both the autonomic and somatic divisions of the nervous system. The clinical features of the diabetic neuropathies vary immensely, and only a minority are associated with pain. The major portion of this review will be dedicated to the most common painful neuropathy, chronic sensorimotor distal symmetrical polyneuropathy (DSPN). This neuropathy has major detrimental effects on its sufferers, confirming an increased risk of foot ulceration and Charcot neuroarthropathy as well as being associated with increased mortality (1).

In addition to DSPN, other rarer neuropathies may also be associated with painful symptoms including acute painful neuropathy that often follows periods of unstable glycemic control, mononeuropathies (e.g., cranial nerve palsies), radiculopathies, and entrapment neuropathies (e.g., carpal tunnel syndrome). By far the most common presentation of diabetic polyneuropathy (over 90%) is typical DSPN or chronic DSPN. […] DSPN results in insensitivity of the feet that predisposes to foot ulceration (1) and/or neuropathic pain (painful DSPN), which can be disabling. […] The onset of DSPN is usually gradual or insidious and is heralded by sensory symptoms that start in the toes and then progress proximally to involve the feet and legs in a stocking distribution. When the disease is well established in the lower limbs in more severe cases, there is upper limb involvement, with a similar progression proximally starting in the fingers. As the disease advances further, motor manifestations, such as wasting of the small muscles of the hands and limb weakness, become apparent. In some cases, there may be sensory loss that the patient may not be aware of, and the first presentation may be a foot ulcer. Approximately 50% of patients with DSPN experience neuropathic symptoms in the lower limbs including uncomfortable tingling (dysesthesia), pain (burning; shooting or “electric-shock like”; lancinating or “knife-like”; “crawling”, or aching etc., in character), evoked pain (allodynia, hyperesthesia), or unusual sensations (such as a feeling of swelling of the feet or severe coldness of the legs when clearly the lower limbs look and feel fine, odd sensations on walking likened to “walking on pebbles” or “walking on hot sand,” etc.). There may be marked pain on walking that may limit exercise and lead to weight gain. Painful DSPN is characteristically more severe at night and often interferes with normal sleep (3). It also has a major impact on the ability to function normally (both mental and physical functioning, e.g., ability to maintain work, mood, and quality of life [QoL]) (3,4). […] The unremitting nature of the pain can be distressing, resulting in mood disorders including depression and anxiety (4). The natural history of painful DSPN has not been well studied […]. However, it is generally believed that painful symptoms may persist over the years (5), occasionally becoming less prominent as the sensory loss worsens (6).”

“There have been relatively few epidemiological studies that have specifically examined the prevalence of painful DSPN, which range from 10–26% (79). In a recent study of a large cohort of diabetic patients receiving community-based health care in northwest England (n = 15,692), painful DSPN assessed using neuropathy symptom and disability scores was found in 21% (7). In one population-based study from Liverpool, U.K., the prevalence of painful DSPN assessed by a structured questionnaire and examination was estimated at 16% (8). Notably, it was found that 12.5% of these patients had never reported their symptoms to their doctor and 39% had never received treatment for their pain (8), indicating that there may be considerable underdiagnosis and undertreatment of painful neuropathic symptoms compared with other aspects of diabetes management such as statin therapy and management of hypertension. Risk factors for DSPN per se have been extensively studied, and it is clear that apart from poor glycemic control, cardiovascular risk factors play a prominent role (10): risk factors for painful DSPN are less well known.”

“A broad spectrum of presentations may occur in patients with DSPN, ranging from one extreme of the patient with very severe painful symptoms but few signs, to the other when patients may present with a foot ulcer having lost all sensation without ever having any painful or uncomfortable symptoms […] it is well recognized that the severity of symptoms may not relate to the severity of the deficit on clinical examination (1). […] Because DSPN is a diagnosis of exclusion, a careful clinical history and a peripheral neurological and vascular examination of the lower limbs are essential to exclude other causes of neuropathic pain and leg/foot pain such as peripheral vascular disease, arthritis, malignancy, alcohol abuse, spinal canal stenosis, etc. […] Patients with asymmetrical symptoms and/or signs (such as loss of an ankle jerk in one leg only), rapid progression of symptoms, or predominance of motor symptoms and signs should be carefully assessed for other causes of the findings.”

“The fact that diabetes induces neuropathy and that in a proportion of patients this is accompanied by pain despite the loss of input and numbness, suggests that marked changes occur in the processes of pain signaling in the peripheral and central nervous system. Neuropathic pain is characterized by ongoing pain together with exaggerated responses to painful and nonpainful stimuli, hyperalgesia, and allodynia. […] the changes seen suggest altered peripheral signaling and central compensatory changes perhaps driven by the loss of input. […] Very clear evidence points to the key role of changes in ion channels as a consequence of nerve damage and their roles in the disordered activity and transduction in damaged and intact fibers (50). Sodium channels depolarize neurons and generate an action potential. Following damage to peripheral nerves, the normal distribution of these channels along a nerve is disrupted by the neuroma and “ectopic” activity results from the accumulation of sodium channels at or around the site of injury. Other changes in the distribution and levels of these channels are seen and impact upon the pattern of neuronal excitability in the nerve. Inherited pain disorders arise from mutated sodium channels […] and polymorphisms in this channel impact on the level of pain in patients, indicating that inherited differences in channel function might explain some of the variability in pain between patients with DSPN (53). […] Where sodium channels act to generate action potentials, potassium channels serve as the molecular brakes of excitable cells, playing an important role in modulating neuronal hyperexcitability. The drug retigabine, a potassium channel opener acting on the channel (KV7, M-current) opener, blunts behavioral hypersensitivity in neuropathic rats (56) and also inhibits C and Aδ-mediated responses in dorsal horn neurons in both naïve and neuropathic rats (57), but has yet to reach the clinic as an analgesic”.

and C fibers terminate primarily in the superficial laminae of the dorsal horn where the large majority of neurons are nociceptive specific […]. Some of these neurons gain low threshold inputs after neuropathy and these cells project predominantly to limbic brain areas […] spinal cord neurons provide parallel outputs to the affective and sensory areas of the brain. Changes induced in these neurons by repeated noxious inputs underpin central sensitization where the resultant hyperexcitability of neurons leads to greater responses to all subsequent inputs — innocuous and noxious — expanded receptive fields and enhanced outputs to higher levels of the brain […] As a consequence of these changes in the sending of nociceptive information within the peripheral nerve and then the spinal cord, the information sent to the brain becomes amplified so that pain ratings become higher. Alongside this, the persistent input into the limbic brain areas such as the amygdala are likely to be causal in the comorbidities that patients often report due to ongoing painful inputs disrupting normal function and generating fear, depression, and sleep problems […]. Of course, many patients report that their pains are worse at night, which may be due to nocturnal changes in these central pain processing areas. […] overall, the mechanisms of pain in diabetic neuropathy extend from altered channel function in peripheral nerves through enhanced spinal processing and finally to changes in many higher centers”.

Pharmacological treatment of painful DSPN is not entirely satisfactory because currently available drugs are often ineffective and complicated by adverse events. Tricyclic compounds (TCAs) have been used as first-line agents for many years, but their use is limited by frequent side effects that may be central or anticholinergic, including dry mouth, constipation, sweating, blurred vision, sedation, and orthostatic hypotension (with the risk of falls particularly in elderly patients). […] Higher doses have been associated with an increased risk of sudden cardiac death, and caution should be taken in any patient with a history of cardiovascular disease (65). […] The selective serotonin noradrenalin reuptake inhibitors (SNRI) duloxetine and venlafaxine have been used for the management of painful DSPN (65). […] there have been several clinical trials involving pregabalin in painful DSPN, and these showed clear efficacy in management of painful DSPN (69). […] The side effects include dizziness, somnolence, peripheral edema, headache, and weight gain.”

A major deficiency in the area of the treatment of neuropathic pain in diabetes is the relative lack of comparative or combination studies. Virtually all previous trials have been of active agents against placebo, whereas there is a need for more studies that compare a given drug with an active comparator and indeed lower-dose combination treatments (64). […] The European Federation of Neurological Societies proposed that first-line treatments might comprise of TCAs, SNRIs, gabapentin, or pregabalin (71). The U.K. National Institute for Health and Care Excellence guidelines on the management of neuropathic pain in nonspecialist settings proposed that duloxetine should be the first-line treatment with amitriptyline as an alternative, and pregabalin as a second-line treatment for painful DSPN (72). […] this recommendation of duloxetine as the first-line therapy was not based on efficacy but rather cost-effectiveness. More recently, the American Academy of Neurology recommended that pregabalin is “established as effective and should be offered for relief of [painful DSPN] (Level A evidence)” (73), whereas venlafaxine, duloxetine, amitriptyline, gabapentin, valproate, opioids, and capsaicin were considered to be “probably effective and should be considered for treatment of painful DSPN (Level B evidence)” (63). […] this recommendation was primarily based on achievement of greater than 80% completion rate of clinical trials, which in turn may be influenced by the length of the trials. […] the International Consensus Panel on Diabetic Neuropathy recommended TCAs, duloxetine, pregabalin, and gabapentin as first-line agents having carefully reviewed all the available literature regarding the pharmacological treatment of painful DSPN (65), the final drug choice tailored to the particular patient based on demographic profile and comorbidities. […] The initial selection of a particular first-line treatment will be influenced by the assessment of contraindications, evaluation of comorbidities […], and cost (65). […] caution is advised to start at lower than recommended doses and titrate gradually.”

ii. Sex Differences in All-Cause and Cardiovascular Mortality, Hospitalization for Individuals With and Without Diabetes, and Patients With Diabetes Diagnosed Early and Late.

“A challenge with type 2 diabetes is the late diagnosis of the disease because many individuals who meet the criteria are often asymptomatic. Approximately 183 million people, or half of those who have diabetes, are unaware they have the disease (1). Furthermore, type 2 diabetes can be present for 9 to 12 years before being diagnosed and, as a result, complications are often present at the time of diagnosis (3). […] Cardiovascular disease (CVD) is the most common comorbidity associated with diabetes, and with 50% of those with diabetes dying of CVD it is the most common cause of death (1). […] Newfoundland and Labrador has the highest age-standardized prevalence of diabetes in Canada (2), and the age-standardized mortality and hospitalization rates for CVD, AMI, and stroke are some of the highest in the country (21,22). A better understanding of mortality and hospitalizations associated with diabetes for males and females is important to support diabetes prevention and management. Therefore, the objectives of this study were to compare the risk of all-cause, CVD, AMI, and stroke mortality and hospitalizations for males and females with and without diabetes and those with early and late diagnoses of diabetes. […] We conducted a population-based retrospective cohort study including 73,783 individuals aged 25 years or older in Newfoundland and Labrador, Canada (15,152 with diabetes; 9,517 with late diagnoses). […] mean age at baseline was 60.1 years (SD, 14.3 years). […] Diabetes was classified as being diagnosed “early” and “late” depending on when diabetes-related comorbidities developed. Individuals early in the disease course would not have any diabetes-related comorbidities at the time of their case dates. On the contrary, a late-diagnosed diabetes patient would have comorbidities related to diabetes at the time of diagnosis.”

“For males, 20.5% (n = 7,751) had diabetes, whereas 20.6% (n = 7,401) of females had diabetes. […] Males and females with diabetes were more likely to die, to be younger at death, to have a shorter survival time, and to be admitted to the hospital than males and females without diabetes (P < 0.01). When admitted to the hospital, individuals with diabetes stayed longer than individuals without diabetes […] Both males and females with late diagnoses were significantly older at the time of diagnosis than those with early diagnoses […]. Males and females with late diagnoses of diabetes were more likely to be deceased at the end of the study period compared with those with early diagnoses […]. Those with early diagnoses were younger at death compared with those with late diagnoses (P < 0.01); however, median survival time for both males and females with early diagnoses was significantly longer than that of those with late diagnoses (P < 0.01). During the study period, males and females with late diabetes diagnoses were more likely to be hospitalized (P < 0.01) and have a longer length of hospital stay compared with those with early diagnoses (P < 0.01).”

“[T]he hospitalization results show that an early diagnosis […] increase the risk of all-cause, CVD, and AMI hospitalizations compared with individuals without diabetes. After adjusting for covariates, males with late diabetes diagnoses had an increased risk of all-cause and CVD mortality and hospitalizations compared with males without diabetes. Similar findings were found for females. A late diabetes diagnosis was positively associated with CVD mortality (HR 6.54 [95% CI 4.80–8.91]) and CVD hospitalizations (5.22 [4.31–6.33]) for females, and the risk was significantly higher compared with their male counterparts (3.44 [2.47–4.79] and 3.33 [2.80–3.95]).”

iii. Effect of Type 1 Diabetes on Carotid Structure and Function in Adolescents and Young Adults.

I may have discussed some of the results of this study before, but a search of the blog told me that I have not covered the study itself. I thought it couldn’t hurt to add a link and a few highlights here.

“Type 1 diabetes mellitus causes increased carotid intima-media thickness (IMT) in adults. We evaluated IMT in young subjects with type 1 diabetes. […] Participants with type 1 diabetes (N = 402) were matched to controls (N = 206) by age, sex, and race or ethnicity. Anthropometric and laboratory values, blood pressure, and IMT were measured.”

“Youth with type 1 diabetes had thicker bulb IMT, which remained significantly different after adjustment for demographics and cardiovascular risk factors. […] Because the rate of progression of IMT in healthy subjects (mean age, 40 years) in the Bogalusa Heart study was 0.017–0.020 mm/year (4), our difference of 0.016 mm suggests that our type 1 diabetic subjects had a vascular age 1 year advanced from their chronological age. […] adjustment for HbA1c ablated the case-control difference in IMT, suggesting that the thicker carotid IMT in the subjects with diabetes could be attributed to diabetes-related hyperglycemia.”

“In the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study, progression of IMT over the course of 6 years was faster in subjects with type 1 diabetes, yielding a thicker final IMT in cases (5). There was no difference in IMT at baseline. However, DCCT/EDIC did not image the bulb, which is likely the earliest site of thickening according to the Bogalusa Heart Study […] Our analyses reinforce the importance of imaging the carotid bulb, often the site of earliest detectible subclinical atherosclerosis in youth. The DCCT/EDIC study demonstrated that the intensive treatment group had a slower progression of IMT (5) and that mean HbA1c levels explained most of the differences in IMT progression between treatment groups (12). One longitudinal study of youth found children with type 1 diabetes who had progression of IMT over the course of 2 years had higher HbA1c (13). Our data emphasize the role of diabetes-related hyperglycemia in increasing IMT in youth with type 1 diabetes. […] In summary, our study provides novel evidence that carotid thickness is increased in youth with type 1 diabetes compared with healthy controls and that this difference is not accounted for by traditional cardiovascular risk factors. Better control of diabetes-related hyperglycemia may be needed to reduce future cardiovascular disease.”

iv. Factors Associated With Microalbuminuria in 7,549 Children and Adolescents With Type 1 Diabetes in the T1D Exchange Clinic Registry.

“Elevated urinary albumin excretion is an early sign of diabetic kidney disease (DKD). The American Diabetes Association (ADA) recommends screening for microalbuminuria (MA) annually in people with type 1 diabetes after 10 years of age and 5 years of diabetes duration, with a diagnosis of MA requiring two of three tests to be abnormal (1). Early diagnosis of MA is important because effective treatments exist to limit the progression of DKD (1). However, although reduced rates of MA have been reported over the past few decades in some (24) but not all (5,6) studies, it has been suggested that the development of proteinuria has not been prevented but, rather, has been delayed by ∼10 years and that further improvements in care are needed (7).

Limited data exist on the frequency of a clinical diagnosis of MA in the pediatric population with type 1 diabetes in the U.S. Our aim was to use the data from the T1D Exchange clinic registry to assess factors associated with MA in 7,549 children and adolescents with type 1 diabetes.”

“The analysis cohort included 7,549 participants, with mean age of 13.8 ± 3.5 years (range 2 to 19), mean age at type 1 diabetes onset of 6.9 ± 3.9 years, and mean diabetes duration of 6.5 ± 3.7 years; 49% were female. The racial/ethnic distribution was 78% non-Hispanic white, 6% non-Hispanic black, 10% Hispanic, and 5% other. The average of all HbA1c levels (for up to the past 13 years) was 8.4 ± 1.3% (69 ± 13.7 mmol/mol) […]. MA was present in 329 of 7,549 (4.4%) participants, with a higher frequency associated with longer diabetes duration, higher mean glycosylated hemoglobin (HbA1c) level, older age, female sex, higher diastolic blood pressure (BP), and lower BMI […] increasing age [was] mainly associated with an increase in the frequency of MA when HbA1c was ≥9.5% (≥80 mmol/mol). […] MA was uncommon (<2%) among participants with HbA1c <7.5% (<58 mmol/mol). Of those with MA, only 36% were receiving ACEI/ARB treatment. […] Our results provide strong support for prior literature in emphasizing the importance of good glycemic and BP control, particularly as diabetes duration increases, in order to reduce the risk of DKD.

v. Secular Changes in the Age-Specific Prevalence of Diabetes Among U.S. Adults: 1988–2010.

“This study included 22,586 adults sampled in three periods of the National Health and Nutrition Examination Survey (1988–1994, 1999–2004, and 2005–2010). Diabetes was defined as having self-reported diagnosed diabetes or having a fasting plasma glucose level ≥126 mg/dL or HbA1c ≥6.5% (48 mmol/mol). […] The number of adults with diabetes increased by 75% from 1988–1994 to 2005–2010. After adjusting for sex, race/ethnicity, and education level, the prevalence of diabetes increased over the two decades across all age-groups. Younger adults (20–34 years of age) had the lowest absolute increase in diabetes prevalence of 1.0%, followed by middle-aged adults (35–64) at 2.7% and older adults (≥65) at 10.0% (all P < 0.001). Comparing 2005–2010 with 1988–1994, the adjusted prevalence ratios (PRs) by age-group were 2.3, 1.3, and 1.5 for younger, middle-aged, and older adults, respectively (all P < 0.05). After additional adjustment for body mass index (BMI), waist-to-height ratio (WHtR), or waist circumference (WC), the adjusted PR remained statistically significant only for adults ≥65 years of age.

CONCLUSIONS During the past two decades, the prevalence of diabetes increased across all age-groups, but adults ≥65 years of age experienced the largest increase in absolute change. Obesity, as measured by BMI, WHtR, or WC, was strongly associated with the increase in diabetes prevalence, especially in adults <65.”

The crude prevalence of diabetes changed from 8.4% (95% CI 7.7–9.1%) in 1988–1994 to 12.1% (11.3–13.1%) in 2005–2010, with a relative increase of 44.8% (28.3–61.3%) between the two survey periods. There was less change of prevalence of undiagnosed diabetes (P = 0.053). […] The estimated number (in millions) of adults with diabetes grew from 14.9 (95% CI 13.3–16.4) in 1988–1994 to 26.1 (23.8–28.3) in 2005–2010, resulting in an increase of 11.2 prevalent cases (a 75.5% [52.1–98.9%] increase). Younger adults contributed 5.5% (2.5–8.4%), middle-aged adults contributed 52.9% (43.4–62.3%), and older adults contributed 41.7% (31.9–51.4%) of the increased number of cases. In each survey time period, the number of adults with diabetes increased with age until ∼60–69 years; thereafter, it decreased […] the largest increase of cases occurred in middle-aged and older adults.”

vi. The Expression of Inflammatory Genes Is Upregulated in Peripheral Blood of Patients With Type 1 Diabetes.

“Although much effort has been devoted toward discoveries with respect to gene expression profiling in human T1D in the last decade (15), previous studies had serious limitations. Microarray-based gene expression profiling is a powerful discovery platform, but the results must be validated by an alternative technique such as real-time RT-PCR. Unfortunately, few of the previous microarray studies on T1D have been followed by a validation study. Furthermore, most previous gene expression studies had small sample sizes (<100 subjects in each group) that are not adequate for the human population given the expectation of large expression variations among individual subjects. Finally, the selection of appropriate reference genes for normalization of quantitative real-time PCR has a major impact on data quality. Most of the previous studies have used only a single reference gene for normalization. Ideally, gene transcription studies using real-time PCR should begin with the selection of an appropriate set of reference genes to obtain more reliable results (68).

We have previously carried out extensive microarray analysis and identified >100 genes with significantly differential expression between T1D patients and control subjects. Most of these genes have important immunological functions and were found to be upregulated in autoantibody-positive subjects, suggesting their potential use as predictive markers and involvement in T1D development (2). In this study, real-time RT-PCR was performed to validate a subset of the differentially expressed genes in a large sample set of 928 T1D patients and 922 control subjects. In addition to the verification of the gene expression associated with T1D, we also identified genes with significant expression changes in T1D patients with diabetes complications.

“Of the 18 genes analyzed here, eight genes […] had higher expression and three genes […] had lower expression in T1D patients compared with control subjects, indicating that genes involved in inflammation, immune regulation, and antigen processing and presentation are significantly altered in PBMCs from T1D patients. Furthermore, one adhesion molecule […] and three inflammatory genes mainly expressed by myeloid cells […] were significantly higher in T1D patients with complications (odds ratio [OR] 1.3–2.6, adjusted P value = 0.005–10−8), especially those patients with neuropathy (OR 4.8–7.9, adjusted P value <0.005). […] These findings suggest that inflammatory mediators secreted mainly by myeloid cells are implicated in T1D and its complications.

vii. Overexpression of Hemopexin in the Diabetic Eye – A new pathogenic candidate for diabetic macular edema.

“Diabetic retinopathy remains the leading cause of preventable blindness among working-age individuals in developed countries (1). Whereas proliferative diabetic retinopathy (PDR) is the commonest sight-threatening lesion in type 1 diabetes, diabetic macular edema (DME) is the primary cause of poor visual acuity in type 2 diabetes. Because of the high prevalence of type 2 diabetes, DME is the main cause of visual impairment in diabetic patients (2). When clinically significant DME appears, laser photocoagulation is currently indicated. However, the optimal period of laser treatment is frequently passed and, moreover, is not uniformly successful in halting visual decline. In addition, photocoagulation is not without side effects, with visual field loss and impairment of either adaptation or color vision being the most frequent. Intravitreal corticosteroids have been successfully used in eyes with persistent DME and loss of vision after the failure of conventional treatment. However, reinjections are commonly needed, and there are substantial adverse effects such as infection, glaucoma, and cataract formation. Intravitreal anti–vascular endothelial growth factor (VEGF) agents have also found an improvement of visual acuity and decrease of retinal thickness in DME, even in nonresponders to conventional treatment (3). However, apart from local side effects such as endophthalmitis and retinal detachment, the response to treatment of DME by VEGF blockade is not prolonged and is subject to significant variability. For all these reasons, new pharmacological treatments based on the understanding of the pathophysiological mechanisms of DME are needed.”

“Vascular leakage due to the breakdown of the blood-retinal barrier (BRB) is the main event involved in the pathogenesis of DME (4). However, little is known regarding the molecules primarily involved in this event. By means of a proteomic analysis, we have found that hemopexin was significantly increased in the vitreous fluid of patients with DME in comparison with PDR and nondiabetic control subjects (5). Hemopexin is the best characterized permeability factor in steroid-sensitive nephrotic syndrome (6,7). […] T cell–associated cytokines like tumor necrosis factor-α are able to enhance hemopexin production in mesangial cells in vitro, and this effect is prevented by corticosteroids (8). However, whether hemopexin also acts as a permeability factor in the BRB and its potential response to corticosteroids remains to be elucidated. […] the aims of the current study were 1) to compare hemopexin and hemopexin receptor (LDL receptor–related protein [LRP1]) levels in retina and in vitreous fluid from diabetic and nondiabetic patients, 2) to evaluate the effect of hemopexin on the permeability of outer and inner BRB in cell cultures, and 3) to determine whether anti-hemopexin antibodies and dexamethasone were able to prevent an eventual hemopexin-induced hyperpermeability.”

“In the current study, we […] confirmed our previous results obtained by a proteomic approach showing that hemopexin is higher in the vitreous fluid of diabetic patients with DME in comparison with diabetic patients with PDR and nondiabetic subjects. In addition, we provide the first evidence that hemopexin is overexpressed in diabetic eye. Furthermore, we have shown that hemopexin leads to the disruption of RPE [retinal pigment epithelium] cells, thus increasing permeability, and that this effect is prevented by dexamethasone. […] Our findings suggest that hemopexin can be considered a new candidate in the pathogenesis of DME and a new therapeutic target.”

viii. Relationship Between Overweight and Obesity With Hospitalization for Heart Failure in 20,985 Patients With Type 1 Diabetes.

“We studied patients with type 1 diabetes included in the Swedish National Diabetes Registry during 1998–2003, and they were followed up until hospitalization for HF, death, or 31 December 2009. Cox regression was used to estimate relative risks. […] Type 1 diabetes is defined in the NDR as receiving treatment with insulin only and onset at age 30 years or younger. These characteristics previously have been validated as accurate in 97% of cases (11). […] In a sample of 20,985 type 1 diabetic patients (mean age, 38.6 years; mean BMI, 25.0 kg/m2), 635 patients […] (3%) were admitted for a primary or secondary diagnosis of HF during a median follow-up of 9 years, with an incidence of 3.38 events per 1,000 patient-years (95% CI, 3.12–3.65). […] Cox regression adjusting for age, sex, diabetes duration, smoking, HbA1c, systolic and diastolic blood pressures, and baseline and intercurrent comorbidities (including myocardial infarction) showed a significant relationship between BMI and hospitalization for HF (P < 0.0001). In reference to patients in the BMI 20–25 kg/m2 category, hazard ratios (HRs) were as follows: HR 1.22 (95% CI, 0.83–1.78) for BMI <20 kg/m2; HR 0.94 (95% CI, 0.78–1.12) for BMI 25–30 kg/m2; HR 1.55 (95% CI, 1.20–1.99) for BMI 30–35 kg/m2; and HR 2.90 (95% CI, 1.92–4.37) for BMI ≥35 kg/m2.

CONCLUSIONS Obesity, particularly severe obesity, is strongly associated with hospitalization for HF in patients with type 1 diabetes, whereas no similar relation was present in overweight and low body weight.”

“In contrast to type 2 diabetes, obesity is not implicated as a causal factor in type 1 diabetes and maintaining normal weight is accordingly less of a focus in clinical practice of patients with type 1 diabetes. Because most patients with type 2 diabetes are overweight or obese and glucose levels can normalize in some patients after weight reduction, this is usually an important part of integrated diabetes care. Our findings indicate that given the substantial risk of cardiovascular disease in type 1 diabetic patients, it is crucial for clinicians to also address weight issues in type 1 diabetes. Because many patients are normal weight when diabetes is diagnosed, careful monitoring of weight with a view to maintaining normal weight is probably more essential than previously thought. Although overweight was not associated with an increased risk of HF, higher BMI levels probably increase the risk of future obesity. Our finding that 71% of patients with BMI >35 kg/m2 were women is potentially important, although this should be tested in other populations given that it could be a random finding. If not random, especially because the proportion was much higher than in the entire cohort (45%), then it may indicate that severe obesity is a greater problem in women than in men with type 1 diabetes.”

November 30, 2017 Posted by | Cardiology, Diabetes, Genetics, Molecular biology, Nephrology, Neurology, Ophthalmology, Pharmacology, Studies | Leave a comment

A few diabetes papers of interest

i. Impact of Sex and Age at Onset of Diabetes on Mortality From Ischemic Heart Disease in Patients With Type 1 Diabetes.

“The study examined long-term IHD-specific mortality in a Finnish population-based cohort of patients with early-onset (0–14 years) and late-onset (15–29 years) T1D (n = 17,306). […] Follow-up started from the time of diagnosis of T1D and ended either at the time of death or at the end of 2011. […] ICD codes used to define patients as having T1D were 2500B–2508B, E10.0–E10.9, or O24.0. […] The median duration of diabetes was 24.4 (interquartile range 17.6–32.2) years. Over a 41-year study period totaling 433,782 person-years of follow-up, IHD accounted for 27.6% of the total 1,729 deaths. Specifically, IHD was identified as the cause of death in 478 patients, in whom IHD was the primary cause of death in 303 and a contributory cause in 175. […] Within the early-onset cohort, the average crude mortality rate in women was 33.3% lower than in men (86.3 [95% CI 65.2–112.1] vs. 128.2 [104.2–156.1] per 100,000 person-years, respectively, P = 0.02). When adjusted for duration of diabetes and the year of diabetes diagnosis, the mortality RR between women and men of 0.64 was only of borderline significance (P = 0.05) […]. In the late-onset cohort, crude mortality in women was, on average, only one-half that of men (117.2 [92.0–147.1] vs. 239.7 [210.9–271.4] per 100,000 person-years, respectively, P < 0.0001) […]. An RR of 0.43 remained highly significant after adjustment for duration of diabetes and year of diabetes diagnosis. Every year of duration of diabetes increased the risk 10–13%”

“The number of deaths from IHD in the patients with T1D were compared with the number of deaths from IHD in the background population, and the SMRs were calculated. For the total cohort (early and late onset pooled), the SMR was 7.2 (95% CI 6.4–8.0) […]. In contrast to the crude mortality rates, the SMRs were higher in women (21.6 [17.2–27.0]) than in men (5.8 [5.1–6.6]). When stratified by the age at onset of diabetes, the SMR was considerably higher in patients with early onset (16.9 [13.5–20.9]) than in those with late onset (5.9 [5.2–6.8]). In both the late- and the early-onset cohorts, there was a striking difference in the SMRs between women and men, and this was especially evident in the early-onset cohort where the SMR for women was 52.8 (36.3–74.5) compared with 12.1 (9.2–15.8) for men. This higher risk of death from IHD compared with the background population was evident in all women, regardless of age. However, the most pronounced effect was seen in women in the early-onset cohort <40 years of age, who were 83 times more likely to die of IHD than the age-matched women in the background population. This compares with a 37 times higher risk of death from IHD in women aged >40 years. The corresponding SMRs for men aged <40 and ≥40 years were 19.4 and 8.5, respectively.”

“Overall, the 40-year cumulative mortality for IHD was 8.8% (95% CI 7.9–9.7%) in all patients […] The 40-year cumulative IHD mortality in the early-onset cohort was 6.3% (4.8–7.8%) for men and 4.5% (3.1–5.9%) for women (P = 0.009 by log-rank test) […]. In the late-onset cohort, the corresponding cumulative mortality rates were 16.6% (14.3–18.7%) in men and 8.5% (6.5–10.4%) in women (P < 0.0001 by log-rank test)”

“The major findings of the current study are that women with early-onset T1D are exceptionally vulnerable to dying from IHD, which is especially evident in those receiving a T1D diagnosis during the prepubertal and pubertal years. Crude mortality rates were similar for women compared with men, highlighting the loss of cardioprotection in women. […] Although men of all ages have greater crude mortality rates than women regardless of the age at onset of T1D, the current study shows that mortality from IHD attributable to diabetes is much more pronounced in women than in men. […] it is conceivable that one of the underlying reasons for the loss of female sex as a protective factor against the development of CVD in the setting of diabetes may be the loss of ovarian hormones. Indeed, women with T1D have been shown to have reduced levels of plasma estradiol compared with age-matched nondiabetic women (23) possibly because of idiopathic ovarian failure or dysregulation of the hypothalamic-pituitary-ovarian axis.”

“One of the novelties of the present study is that the risk of death from IHD highly depends on the age at onset of T1D. The data show that the SMR was considerably higher in early-onset (0–14 years) than in late-onset (15–29 years) T1D in both sexes. […] the risk of dying from IHD is high in both women and men receiving a diagnosis of T1D at a young age.

ii. Microalbuminuria as a Risk Predictor in Diabetes: The Continuing Saga.

“The term “microalbuminuria” (MA) originated in 1964 when Professor Harry Keen first used it to signify a small amount of albumin in the urine of patients with type 1 diabetes (1). […] Whereas early research focused on the relevance of MA as a risk factor for diabetic kidney disease, research over the past 2 decades has shifted to examine whether MA is a true risk factor. To appreciate fully the contribution of MA to overall cardiorenal risk, it is important to distinguish between a risk factor and risk marker. A risk marker is a variable that identifies a pathophysiological state, such as inflammation or infection, and is not necessarily involved, directly or causally, in the genesis of a specified outcome (e.g., association of a cardiovascular [CV] event with fever, high-sensitivity C-reactive protein [hs-CRP], or MA). Conversely, a risk factor is involved clearly and consistently with the cause of a specified event (e.g., a CV event associated with persistently elevated blood pressure or elevated levels of LDL). Both a risk marker and a risk factor can predict an adverse outcome, but only one lies within the causal pathway of a disease. Moreover, a reduction (or alteration in a beneficial direction) of a risk factor (i.e., achievement of blood pressure goal) generally translates into a reduction of adverse outcomes, such as CV events; this is not necessarily true for a risk marker.”

“The data sources included in this article were all PubMed-referenced articles in English-language peer-reviewed journals since 1964. Studies selected had to have a minimum follow-up of 1 year; include at least 100 participants; be either a randomized trial, a systematic review, a meta-analysis, or a large observational cohort study in patients with any type of diabetes; or be trials of high CV risk that included at least 50% of patients with diabetes. All studies had to assess changes in MA tied to CV or CKD outcomes and not purely reflect changes in MA related to blood pressure, unless they were mechanistic studies. On the basis of these inclusion criteria, 31 studies qualified and provide the data used for this review.”

“Early studies in patients with diabetes supported the concept that as MA increases to higher levels, the risk of CKD progression and CV risk also increases […]. Moreover, evidence from epidemiological studies in patients with diabetes suggested that the magnitude of urine albumin excretion should be viewed as a continuum of CV risk, with the lower the albumin excretion, the lower the CV risk (15,16). However, MA values can vary daily up to 100% (11). These large biological variations are a result of a variety of conditions, with a central core tied to inflammation associated with factors ranging from increased blood pressure variability, high blood glucose levels, high LDL cholesterol, and high uric acid levels to high sodium ingestion, smoking, and exercise (17) […]. Additionally, any febrile illness, regardless of etiology, will increase urine albumin excretion (18). Taken together, these data support the concept that MA is highly variable and that values over a short time period (i.e., 3–6 months) are meaningless in predicting any CV or kidney disease outcome.”

“Initial studies to understand the mechanisms of MA examined changes in glomerular membrane permeability as a key determinant in patients with diabetes […]. Many factors affect the genesis and level of MA, most of which are linked to inflammatory conditions […]. A good evidence base, however, supports the concept that MA directly reflects the amount of inflammation and vascular “leakiness” present in patients with diabetes (16,18,19).

More recent studies have found a number of other factors that affect glomerular permeability by modifying cytokines that affect permeability. Increased amounts of glycated albumin reduce glomerular nephrin and increase vascular endothelial growth factor (20). Additionally, increases in sodium intake (21) as well as intraglomerular pressure secondary to high protein intake or poorly controlled blood pressure (22,23) increase glomerular permeability in diabetes and, hence, MA levels.

In individuals with diabetes, albumin is glycated and associated with the generation of reactive oxygen species. In addition, many other factors such as advanced glycation end products, reactive oxygen species, and other cellular toxins contribute to vascular injury. Once such injury occurs, the effect of pressor hormones, such as angiotensin II, is magnified, resulting in a faster progression of vascular injury. The end result is direct injury to the vascular smooth muscle cells, endothelial cells, and visceral epithelial cells (podocytes) of the glomerular capillary wall membrane as well as to the proximal tubular cells and podocyte basement membrane of the nephron (20,24,25). All these contribute to the development of MA. […] better glycemic control is associated with far lower levels of inflammatory markers (31).”

“MA is accepted as a CV risk marker for myocardial infarction and stroke, regardless of diabetes status. […] there is good evidence in those with type 2 diabetes that the presence of MA >100 mg/day is associated with higher CV events and greater likelihood of kidney disease development (6). Evidence for this association comes from many studies and meta-analyses […] a meta-analysis by Perkovic et al. (37) demonstrated a dose-response relationship between the level of albuminuria and CV risk. In this meta-analysis, individuals with MA were at 50% greater risk of coronary heart disease (risk ratio 1.47 [95% CI 1.30–1.66]) than those without. Those with macroalbuminuria (i.e., >300 mg/day) had more than a twofold risk for coronary heart disease (risk ratio 2.17 [95% CI 1.87–2.52]) (37). Despite these data indicating a higher CV risk in patients with MA regardless of diabetes status and other CV risk factors, there is no consensus that the addition of MA to conventional CV risk stratification for the general population (e.g., Framingham or Reynolds scoring systems) is of any clinical value, and that includes patients with diabetes (38).”

“Given that MA was evaluated in a post hoc manner in almost all interventional studies, it is likely that the reduction in MA simply reflects the effects of either renin-angiotensin system (RAS) blockade on endothelial function or significant blood pressure reduction rather than the MA itself being implicated as a CV disease risk factor (18). […] associations of lowering MA with angiotensin-converting enzyme (ACE) inhibitors or angiotensin receptor blockers (ARBs) does not prove a direct benefit on CV event lowering associated with MA reduction in diabetes. […] Four long-term, appropriately powered trials demonstrated an inverse relationship between reductions in MA and primary event rates for CV events […]. Taken together, these studies support the concept that MA is a risk marker in diabetes and is consistent with data of other inflammatory markers, such as hs-CRP [here’s a relevant link – US], such that the higher the level, the higher the risk (15,39,42). The importance of MA as a CV risk marker is exemplified further by another meta-analysis that showed that MA has a similar magnitude of CV risk as hs-CRP and is a better predictor of CV events (43). Thus, the data supporting MA as a risk marker for CV events are relatively consistent, clearly indicate that an association exists, and help to identify the presence of underlying inflammatory states, regardless of etiology.”

“In people with early stage nephropathy (i.e., stage 2 or 3a [GFR 45–89 mL/min/1.73 m2]) and MA, there is no clear benefit on slowing GFR decline by reducing MA with drugs that block the RAS independent of lowering blood pressure (16). This is exemplified by many trials […]. Thus, blood pressure lowering is the key goal for all patients with early stage nephropathy associated with normoalbuminuria or MA. […] When albuminuria levels are in the very high or macroalbuminuria range (i.e., >300 mg/day), it is accepted that the patient has CKD and is likely to progress ultimately to ESRD, unless they die of a CV event (39,52). However, only one prospective randomized trial evaluated the role of early intervention to reduce blood pressure with an ACE inhibitor versus a calcium channel blocker in CKD progression by assessing change in MA and creatinine clearance in people with type 2 diabetes (Appropriate Blood Pressure Control in Diabetes [ABCD] trial) (23). After >7 years of follow-up, there was no relationship between changes in MA and CKD progression. Moreover, there was regression to the mean of MA.”

“Many observational studies used development of MA as indicating the presence of early stage CKD. Early studies by the individual groups of Mogensen and Parving demonstrated a relationship between increases in MA and progression to nephropathy in type 1 diabetes. These groups also showed that use of ACE inhibitors, blood pressure reduction, and glucose control reduced MA (9,58,59). However, more recent studies in both type 1 and type 2 diabetes demonstrated that only a subgroup of patients progress from MA to >300 mg/day albuminuria, and this subgroup accounts for those destined to progress to ESRD (29,32,6063). Thus, the presence of MA alone is not predictive of CKD progression. […] some patients with type 2 diabetes progress to ESRD without ever having developed albuminuria levels of ≥300 mg/day (67). […] Taken together, data from outcome trials, meta-analyses, and observations demonstrate that MA [Micro-Albuminuria] alone is not synonymous with the presence of clearly defined CKD [Chronic Kidney Disease] in diabetes, although it is used as part of the criteria for the diagnosis of CKD in the most recent CKD classification and staging (71). Note that only a subgroup of ∼25–30% of people with diabetes who also have MA will likely progress to more advanced stages of CKD. Predictors of progression to ESRD, apart from family history, and many years of poor glycemic and blood pressure control are still not well defined. Although there are some genetic markers, such as CUBN and APOL1, their use in practice is not well established.”

“In the context of the data presented in this article, MA should be viewed as a risk marker associated with an increase in CV risk and for kidney disease, but its presence alone does not indicate established kidney disease, especially if the eGFR is well above 60 mL/min/1.73 m2. Increases in MA, with blood pressure and other CV risk factors controlled, are likely but not proven to portend a poor prognosis for CKD progression over time. Achieving target blood pressure (<140/80 mmHg) and target HbA1c (<7%) should be priorities in treating patients with MA. Recent guidelines from both the American Diabetes Association and the National Kidney Foundation provide a strong recommendation for using agents that block the RAS, such as ACE inhibitors and ARBs, as part of the regimen for those with albuminuria levels >300 mg/day but not MA (73). […] maximal antialbuminuric effects will [however] not be achieved with these agents unless a low-sodium diet is strictly followed.”

iii. The SEARCH for Diabetes in Youth Study: Rationale, Findings, and Future Directions.

“The SEARCH for Diabetes in Youth (SEARCH) study was initiated in 2000, with funding from the Centers for Disease Control and Prevention and support from the National Institute of Diabetes and Digestive and Kidney Diseases, to address major knowledge gaps in the understanding of childhood diabetes. SEARCH is being conducted at five sites across the U.S. and represents the largest, most diverse study of diabetes among U.S. youth. An active registry of youth diagnosed with diabetes at age <20 years allows the assessment of prevalence (in 2001 and 2009), annual incidence (since 2002), and trends by age, race/ethnicity, sex, and diabetes type. Prevalence increased significantly from 2001 to 2009 for both type 1 and type 2 diabetes in most age, sex, and race/ethnic groups. SEARCH has also established a longitudinal cohort to assess the natural history and risk factors for acute and chronic diabetes-related complications as well as the quality of care and quality of life of persons with diabetes from diagnosis into young adulthood. […] This review summarizes the study methods, describes key registry and cohort findings and their clinical and public health implications, and discusses future directions.”

“SEARCH includes a registry and a cohort study […]. The registry study identifies incident cases each year since 2002 through the present with ∼5.5 million children <20 years of age (∼6% of the U.S. population <20 years) under surveillance annually. Approximately 3.5 million children <20 years of age were under surveillance in 2001 at the six SEARCH recruitment centers, with approximately the same number at the five centers under surveillance in 2009.”

“The prevalence of all types of diabetes was 1.8/1,000 youth in 2001 and was 2.2/1,000 youth in 2009, which translated to at least 154,000 children/youth in the U.S. with diabetes in 2001 (5) and at least 192,000 in 2009 (6). Overall, between 2001 and 2009, prevalence of type 1 diabetes in youth increased by 21.1% (95% CI 15.6–27.0), with similar increases for boys and girls and in most racial/ethnic and age groups (2) […]. The prevalence of type 2 diabetes also increased significantly over the same time period by 30.5% (95% CI 17.3–45.1), with increases observed in both sexes, 10–14- and 15–19-year-olds, and among Hispanic and non-Hispanic white and African American youth (2). These data on changes in type 2 are consistent with smaller U.S. studies (711).”

“The incidence of diabetes […] in 2002 to 2003 was 24.6/100,000/year (12), representing ∼15,000 new patients every year with type 1 diabetes and 3,700 with type 2 diabetes, increasing to 18,436 newly diagnosed type 1 and 5,089 with type 2 diabetes in 2008 to 2009 (13). Among non-Hispanic white youth, the incidence of type 1 diabetes increased by 2.7% (95% CI 1.2–4.3) annually between 2002 and 2009. Significant increases were observed among all age groups except the youngest age group (0–4 years) (14). […] The underlying factors responsible for this increase have not yet been identified.”

Over 50% of youth are hospitalized at diabetes onset, and ∼30% of children newly diagnosed with diabetes present with diabetic ketoacidosis (DKA) (19). Prevalence of DKA at diagnosis was three times higher among youth with type 1 diabetes (29.4%) compared with youth with type 2 diabetes (9.7%) and was lowest in Asian/Pacific Islanders (16.2%) and highest among Hispanics (27.0%).”

“A significant proportion of youth with diabetes, particularly those with type 2 diabetes, have very poor glycemic control […]: 17% of youth with type 1 diabetes and 27% of youth with type 2 diabetes had A1C levels ≥9.5% (≥80 mmol/mol). Minority youth were significantly more likely to have higher A1C levels compared with non-Hispanic white youth, regardless of diabetes type. […] Optimal care is an important component of successful long-term management for youth with diabetes. While there are high levels of adherence for some diabetes care indicators such as blood pressure checks (95%), urinary protein tests (83%), and lipid assessments (88%), approximately one-third of youth had no documentation of eye or A1C values at appropriate intervals and therefore were not meeting the American Diabetes Association (ADA)-recommended screening for diabetic control and complications (40). Participants ≥18 years old, particularly those with type 2 diabetes, and minority youth with type 1 diabetes had fewer tests of all kinds performed. […] Despite current treatment options, the prevalence of poor glycemic control is high, particularly among minority youth. Our initial findings suggest that a substantial number of youth with diabetes will develop serious, debilitating complications early in life, which is likely to have significant implications for their quality of life, as well as economic and health care implications.”

“Because recognition of the broader spectrum of diabetes in children and adolescents is recent, there are no gold-standard definitions for differentiating the types of diabetes in this population, either for research or clinical purposes or for public health surveillance. The ADA classification of diabetes as type 1 and type 2 does not include operational definitions for the specific etiologic markers of diabetes type, such as types and numbers of diabetes autoantibodies or measures of insulin resistance, hallmarks of type 1 and 2 diabetes, respectively (43). Moreover, obese adolescents with a clinical phenotype suggestive of type 2 diabetes can present with ketoacidosis (44) or have evidence of autoimmunity (45).”

“Using the ADA framework (43), we operationalized definitions of two main etiologic markers, autoimmunity and insulin sensitivity, to identify four etiologic subgroups based on the presence or absence of markers. Autoimmunity was based on presence of one or more diabetes autoantibodies (GAD65 and IA2). Insulin sensitivity was estimated using clinical variables (A1C, triglyceride level, and waist circumference) from a formula that was highly associated with estimated insulin sensitivity measured using a euglycemic-hyperinsulinemic clamp among youth with type 1 and 2 and normal control subjects (46). Participants were categorized as insulin resistant […] and insulin sensitive (47). Using this approach, 54.5% of SEARCH cases were classified as typical type 1 (autoimmune, insulin-sensitive) diabetes, while 15.9% were classified as typical type 2 (nonautoimmune, insulin-resistant) diabetes. Cases that were classified as autoimmune and insulin-resistant likely represent individuals with type 1 autoimmune diabetes and concomitant obesity, a phenotype becoming more prevalent as a result of the recent increase in the frequency of obesity, but is unlikely to be a distinct etiologic entity.”

“Ten percent of SEARCH participants had no evidence of either autoimmunity or insulin resistance and thus require additional testing, including additional measurements of diabetes-related autoantibodies (only two antibodies were measured in SEARCH) as well as testing for monogenic forms of diabetes to clarify etiology. Among antibody-negative youth, 8% of those tested had a mutation in one or more of the hepatocyte nuclear factor-1α (HNF-1α), glucokinase, and HNF-4α genes, an estimated monogenic diabetes population prevalence of at least 1.2% (48).”

iv. Does the Prevailing Hypothesis That Small-Fiber Dysfunction Precedes Large-Fiber Dysfunction Apply to Type 1 Diabetic Patients?

The short answer is ‘yes, it does’. Some observations from the paper:

“Diabetic sensorimotor polyneuropathy (DSP) is a common complication of diabetes, affecting 28–55% of patients (1). A prospective Finnish study found evidence of probable or definite neuropathy in 8.3% of diabetic patients at the time of diagnosis, 16.7% after 5 years, and 41.9% after 10 years (2). Diabetes-related peripheral neuropathy results in serious morbidity, including chronic neuropathic pain, leg weakness and falls, sensory loss and foot ulceration, and amputation (3). Health care costs associated with diabetic neuropathy were estimated at $10.9 billion in the U.S. in 2003 (4). However, despite the high prevalence of diabetes and DSP, and the important public health implications, there is a lack of serum- or tissue-based biomarkers to diagnose and follow patients with DSP longitudinally. Moreover, numerous attempts at treatment have yielded negative results.”

“DSP is known to cause injury to both large-diameter, myelinated (Aα and Aβ) fibers and small-diameter, unmyelinated nerve (Aδ and C) fibers; however, the sequence of nerve fiber damage remains uncertain. While earlier reports seemed to indicate simultaneous loss of small- and large-diameter nerve fibers, with preserved small/large ratios (5), more recent studies have suggested the presence of early involvement of small-diameter Aδ and C fibers (611). Some suggest a temporal relationship of small-fiber impairment preceding that of large fibers. For example, impairment in the density of the small intraepidermal nerve fibers in symptomatic patients with impaired glucose tolerance (prediabetes) have been observed in the face of normal large-fiber function, as assessed by nerve conduction studies (NCSs) (9,10). In addition, surveys of patients with DSP have demonstrated an overwhelming predominance of sensory and autonomic symptoms, as compared with motor weakness. Again, this has been interpreted as indicative of preferential small-fiber dysfunction (12). Though longitudinal studies are limited, such studies have lead to the current prevailing hypothesis for the natural history of DSP that measures of small-fiber morphology and function decline prior to those of large fibers. One implication of this hypothesis is that small-fiber testing could serve as an earlier, subclinical primary end point in clinical trials investigating interventions for DSP (13).

The hypothesis described above has been investigated exclusively in type 2 diabetic or prediabetic patients. Through the study of a cohort of healthy volunteers and type 1 diabetic subjects […], we had the opportunity to evaluate in cross-sectional analysis the relationship between measures of large-fiber function and small-fiber structure and function. Under the hypothesis that small-fiber abnormalities precede large-fiber dysfunction in the natural history of DSP, we sought to determine if: 1) the majority of subjects who meet criteria for large-fiber dysfunction have concurrent evidence of small-fiber dysfunction and 2) the subset of patients without DSP includes a spectrum with normal small-fiber tests (indicating lack of initiation of nerve injury) as well as abnormal small-fiber tests (indicating incipient DSP).”

“Overall, 57 of 131 (43.5%) type 1 diabetic patients met DSP criteria, and 74 of 131 (56.5%) did not meet DSP criteria. Abnormality of CCM [link] was present in 30 of 57 (52.6%) DSP patients and 6 of 74 (8.1%) type 1 diabetic patients without DSP. Abnormality of CDT [Cooling Detection Thresholds, relevant link] was present in 47 of 56 (83.9%) DSP patients and 17 of 73 (23.3%) without DSP. Abnormality of LDIflare [laser Doppler imaging of heat-evoked flare] was present in 30 of 57 (52.6%) DSP patients and 20 of 72 (27.8%) without DSP. Abnormality of HRV [Heart Rate Variability] was present in 18 of 45 (40.0%) DSP patients and 6 of 70 (8.6%) without DSP. […] sensitivity analysis […] revealed that abnormality of any one of the four small-fiber measures was present in 55 of 57 (96.5%) DSP patients […] and 39 of 74 (52.7%) type 1 diabetic patients without DSP. Similarly, abnormality of any two of the four small-fiber measures was present in 43 of 57 (75.4%) DSP patients […] and 9 of 74 (12.2%) without DSP. Finally, abnormality of either CDT or CCM (with these two tests selected based on their high reliability) was noted in 53 of 57 (93.0%) DSP patients and 21 of 74 (28.4%) patients without DSP […] When DSP was defined based on symptoms and signs plus abnormal sural SNAP [sensory nerve action potential] amplitude or conduction velocity, there were 68 of 131 patients who met DSP criteria and 63 of 131 who did not. Abnormality of any one of the four small-fiber measures was present in 63 of 68 (92.6%) DSP patients and 31 of 63 (49.2%) type 1 diabetic patients without DSP. […] Finally, if DSP was defined based on clinical symptoms and signs alone, with TCNS ≥5, there were 68 of 131 patients who met DSP criteria and 63 of 131 who did not. Abnormality of any one of the four small-fiber measures was present in 62 of 68 (91.2%) DSP patients and 32 of 63 (50.8%) type 1 diabetic patients without DSP.”

“Qualitative analysis of contingency tables shows that the majority of patients with DSP have concurrent evidence of small-fiber dysfunction, and patients without DSP include a spectrum with normal small-fiber tests (indicating lack of initiation of nerve injury) as well as abnormal small-fiber tests. Evidence of isolated large-fiber injury was much less frequent […]. These findings suggest that small-fiber damage may herald the onset of DSP in type 1 diabetes. In addition, the above findings remained true when alternative definitions of DSP were explored in a sensitivity analysis. […] The second important finding was the linear relationships noted between small-fiber structure and function tests (CDT, CNFL, LDIflare, and HRV) […] and the number of NCS abnormalities (a marker of large-fiber function). This might indicate that once the process of large-fiber nerve injury in DSP has begun, damage to large and small nerve fibers occurs simultaneously.”

v. Long-Term Complications and Mortality in Young-Onset Diabetes.

“Records from the Royal Prince Alfred Hospital Diabetes Clinical Database, established in 1986, were matched with the Australian National Death Index to establish mortality outcomes for all subjects until June 2011. Clinical and mortality outcomes in 354 patients with T2DM, age of onset between 15 and 30 years (T2DM15–30), were compared with T1DM in several ways but primarily with 470 patients with T1DM with a similar age of onset (T1DM15–30) to minimize the confounding effect of age on outcome.

RESULTS For a median observation period of 21.4 (interquartile range 14–30.7) and 23.4 (15.7–32.4) years for the T2DM and T1DM cohorts, respectively, 71 of 824 patients (8.6%) died. A significant mortality excess was noted in T2DM15–30 (11 vs. 6.8%, P = 0.03), with an increased hazard for death (hazard ratio 2.0 [95% CI 1.2–3.2], P = 0.003). Death for T2DM15–30 occurred after a significantly shorter disease duration (26.9 [18.1–36.0] vs. 36.5 [24.4–45.4] years, P = 0.01) and at a relatively young age. There were more cardiovascular deaths in T2DM15–30 (50 vs. 30%, P < 0.05). Despite equivalent glycemic control and shorter disease duration, the prevalence of albuminuria and less favorable cardiovascular risk factors were greater in the T2DM15–30 cohort, even soon after diabetes onset. Neuropathy scores and macrovascular complications were also increased in T2DM15–30 (P < 0.0001).

CONCLUSIONS Young-onset T2DM is the more lethal phenotype of diabetes and is associated with a greater mortality, more diabetes complications, and unfavorable cardiovascular disease risk factors when compared with T1DM.

“Only a few previous studies have looked at comparative mortality in T1DM and T2DM onset in patients <30 years of age. In a Swedish study of patients with diabetes aged 15–34 years compared with a general population, the standardized mortality ratio was higher for the T2DM than for the T1DM cohort (2.9 vs. 1.8) (17). […] Recently, Dart et al. (19) examined survival in youth aged 1–18 years with T2DM versus T1DM. Kaplan-Meier analysis revealed a statistically significant lower survival probability for the youth with T2DM, although the number at risk was low after 10 year’s duration. Taken together, these findings are in keeping with the present observations and are supportive evidence for a higher mortality in young-onset T2DM than in T1DM. The majority of deaths appear to be from cardiovascular causes and significantly more so for young T2DM.”

“Although the age of onset of T1DM diabetes is usually in little doubt because of a more abrupt presentation, it is possible that the age of onset of T2DM was in fact earlier than recognized. With a previously published method for estimating time delay until diagnosis of T2DM (26) by plotting the prevalence of retinopathy against duration and extrapolating to a point of zero retinopathy, we found that there is no difference in the slope and intercept of this relationship between the T2DM and the T1DM cohorts […] delay in diagnosis is unlikely to be an explanation for the differences in observed outcome.”

vi. Cardiovascular Risk Factors Are Associated With Increased Arterial Stiffness in Youth With Type 1 Diabetes.

“Increased arterial stiffness independently predicts all-cause and CVD mortality (3), and higher pulse pressure predicts CVD mortality, incidence, and end-stage renal disease development among adults with type 1 diabetes (1,4,5). Several reports have shown that youth and adults with type 1 diabetes have elevated arterial stiffness, though the mechanisms are largely unknown (6). The etiology of advanced atherosclerosis in type 1 diabetes is likely multifactorial, involving metabolic, behavioral, and diabetes-specific cardiovascular (CV) risk factors. Aging, high blood pressure (BP), obesity, the metabolic syndrome (MetS), and type 2 diabetes are the main contributors of sustained increased arterial stiffness in adults (7,8). However, the natural history, the age-related progression, and the possible determinants of increased arterial stiffness in youth with type 1 diabetes have not been studied systematically. […] There are currently no data examining the impact of CV risk factors and their clustering in youth with type 1 diabetes on subsequent CVD morbidity and mortality […]. Thus, the aims of this report were: 1) to describe the progression of arterial stiffness, as measured by pulse wave velocity (PWV), over time, among youth with type 1 diabetes, and 2) to explore the association of CV risk factors and their clustering as MetS with PWV in this cohort.”

“Youth were age 14.5 years (SD 2.8) and had an average disease duration of 4.8 (3.8) years at baseline, 46.3% were female, and 87.6% were of NHW race/ethnicity. At baseline, 10.0% had high BP, 10.9% had a large waist circumference, 11.6% had HDL-c ≤40 mg/dL, 10.9% had a TG level ≥110 mg/dL, and 7.0% had at least two of the above CV risk factors (MetS). In addition, 10.3% had LDL-c ≥130 mg/dL, 72.0% had an HbA1c ≥7.5% (58 mmol/mol), and 9.2% had ACR ≥30 μg/mL. Follow-up measures were obtained on average at age 19.2 years, when the average duration of diabetes was 10.1 (3.9) years.”

“Over an average follow-up period of ∼5 years, there was a statistically significant increase of 0.7 m/s in PWV (from 5.2 to 5.9 m/s), representing an annual increase of 2.8% or 0.145 m/s. […] Based on our data, if this rate of change is stable over time, the estimated average PWV by the time these youth enter their third decade of life will be 11.3 m/s, which was shown to be associated with a threefold increased hazard for major CV events (26). There are no similar studies in youth to compare these findings. In adults, the rate of change in PWV was 0.081 m/s/year in nondiabetic normotensive patients, although it was higher in hypertensive adults (0.147 m/s/year) (7). We also showed that the presence of central adiposity and elevated BP at baseline, as well as clustering of at least two CV risk factors, was associated with significantly worse PWV over time, although these baseline factors did not significantly influence the rate of change in PWV over this period of time. Changes in CV risk factors, specifically increases in central adiposity, LDL-c levels, and worsening glucose control, were independently associated with worse PWV over time. […] Our inability to detect a difference in the rate of change in PWV in our youth with MetS (vs. those without MetS) may be due to several factors, including a combination of a relatively small sample size, short period of follow-up, and young age of the cohort (thus with lower baseline PWV levels).”

 

November 8, 2017 Posted by | Cardiology, Diabetes, Epidemiology, Genetics, Medicine, Nephrology, Neurology, Studies | Leave a comment

A few diabetes papers of interest

i. Chronic Fatigue in Type 1 Diabetes: Highly Prevalent but Not Explained by Hyperglycemia or Glucose Variability.

“Fatigue is a classical symptom of hyperglycemia, but the relationship between chronic fatigue and diabetes has not been systematically studied. […] glucose control [in diabetics] is often suboptimal with persistent episodes of hyperglycemia that may result in sustained fatigue. Fatigue may also sustain in diabetic patients because it is associated with the presence of a chronic disease, as has been demonstrated in patients with rheumatoid arthritis and various neuromuscular disorders (2,3).

It is important to distinguish between acute and chronic fatigue, because chronic fatigue, defined as severe fatigue that persists for at least 6 months, leads to substantial impairments in patients’ daily functioning (4,5). In contrast, acute fatigue can largely vary during the day and generally does not cause functional impairments.

Literature provides limited evidence for higher levels of fatigue in diabetic patients (6,7), but its chronicity, impact, and determinants are unknown. In various chronic diseases, it has been proven useful to distinguish between precipitating and perpetuating factors of chronic fatigue (3,8). Illness-related factors trigger acute fatigue, while other factors, often cognitions and behaviors, cause fatigue to persist. Sleep disturbances, low self-efficacy concerning fatigue, reduced physical activity, and a strong focus on fatigue are examples of these fatigue-perpetuating factors (810). An episode of hyperglycemia or hypoglycemia could trigger acute fatigue for diabetic patients (11,12). However, variations in blood glucose levels might also contribute to chronic fatigue, because these variations continuously occur.

The current study had two aims. First, we investigated the prevalence and impact of chronic fatigue in a large sample of type 1 diabetic (T1DM) patients and compared the results to a group of age- and sex-matched population-based controls. Secondly, we searched for potential determinants of chronic fatigue in T1DM.”

“A significantly higher percentage of T1DM patients were chronically fatigued (40%; 95% CI 34–47%) than matched controls (7%; 95% CI 3–10%). Mean fatigue severity was also significantly higher in T1DM patients (31 ± 14) compared with matched controls (17 ± 9; P < 0.001). T1DM patients with a comorbidity_mr [a comorbidity affecting patients’ daily functioning, based on medical records – US] or clinically relevant depressive symptoms [based on scores on the Beck Depression Inventory for Primary Care – US] were significantly more often chronically fatigued than patients without a comorbidity_mr (55 vs. 36%; P = 0.014) or without clinically relevant depressive symptoms (88 vs. 31%; P < 0.001). Patients who reported neuropathy, nephropathy, or cardiovascular disease as complications of diabetes were more often chronically fatigued […] Chronically fatigued T1DM patients were significantly more impaired compared with nonchronically fatigued T1DM patients on all aspects of daily functioning […]. Fatigue was the most troublesome symptom of the 34 assessed diabetes-related symptoms. The five most troublesome symptoms were overall sense of fatigue, lack of energy, increasing fatigue in the course of the day, fatigue in the morning when getting up, and sleepiness or drowsiness”.

“This study establishes that chronic fatigue is highly prevalent and clinically relevant in T1DM patients. While current blood glucose level was only weakly associated with chronic fatigue, cognitive behavioral factors were by far the strongest potential determinants.”

“Another study found that type 2 diabetic, but not T1DM, patients had higher levels of fatigue compared with healthy controls (7). This apparent discrepancy may be explained by the relatively small sample size of this latter study, potential selection bias (patients were not randomly selected), and the use of a different fatigue questionnaire.”

“Not only was chronic fatigue highly prevalent, fatigue also had a large impact on T1DM patients. Chronically fatigued T1DM patients had more functional impairments than nonchronically fatigued patients, and T1DM patients considered fatigue as the most burdensome diabetes-related symptom.

Contrary to what was expected, there was at best a weak relationship between blood glucose level and chronic fatigue. Chronically fatigued T1DM patients spent slightly less time in hypoglycemia, but average glucose levels, glucose variability, hyperglycemia, or HbA1c were not related to chronic fatigue. In type 2 diabetes mellitus also, no relationship was found between fatigue and HbA1c (7).”

“Regarding demographic characteristics, current health status, diabetes-related factors, and fatigue-related cognitions and behaviors as potential determinants of chronic fatigue, we found that sleeping problems, physical activity, self-efficacy concerning fatigue, age, depression, and pain were significantly associated with chronic fatigue in T1DM. Although depression was strongly related, it could not completely explain the presence of chronic fatigue (38), as 31% was chronically fatigued without having clinically relevant depressive symptoms.”

Some comments may be worth adding here. It’s important to note to people who may not be aware of this that although chronic fatigue is a weird entity that’s hard to get a handle on (and, to be frank, is somewhat controversial), specific organic causes have been identified that greatly increases the risk. Many survivors of cancer experience chronic fatigue (see e.g. this paper, or wikipedia), and chronic fatigue is also not uncommon in a kidney failure setting (“The silence of renal disease creeps up on us (doctors and patients). Do not dismiss odd chronic symptoms such as fatigue or ‘not being quite with it’ without considering checking renal function” (Oxford Handbook of Clinical Medicine, 9th edition. My italics – US)). As observed above, linkage with RA and some neuromuscular disorders has also been observed. The brief discussion of related topics in Houghton & Grey made it clear to me that some people with chronic fatigue are almost certainly suffering from an organic illness which has not been diagnosed or treated. Here’s a relevant quote from that book’s coverage: “it is unusual to find a definite organic cause for fatigue. However, consider anaemia, thyroid dysfunction, Addison’s disease and hypopituitarism.” It’s sort of neat, if you think about the potential diabetes-fatigue link investigated by the guys above, that some of these diseases are likely to be relevant, as type 1 diabetics are more likely to develop them (anemia is not linked to diabetes, as far as I know, and I believe the relationship between autoimmune hypophysitis – which is a cause of hypopituitarism – and type 1 diabetes is at best unclear, but the others are definitely involved) due to their development being caused by some of the same genetic mutations which cause type 1 diabetes; the combinations of some of these diseases even have fancy names of their own, like ‘Type I Polyglandular Autoimmune Syndrome’ and ‘Schmidt Syndrome’ (if you’re interested here are a couple of medscape links). It’s noteworthy that although most of these diseases are uncommon in the general population, their incidence/prevalence is likely to be greatly increased in type 1 diabetics due to the common genetic pathways at play (variants regulating T-cell function seem to be important, but there’s no need to go into these details here). Sperling et al. note in their book that: “Hypothyroid or hyperthyroid AITD [autoimmune thyroid disease] has been observed in 10–24% of patients with type 1 diabetes”. In one series including 151 patients with APS [/PAS]-2, when they looked at disease combinations they found that: “Of combinations of the component diseases, [type 1] diabetes with thyroid disease was the most common, occurring in 33%. The second, diabetes with adrenal insufficiency, made up 15%” (same source).

It seems from estimates like these likely that a not unsubstantial proportion of type 1 diabetics over time go on to develop other health problems that might if unaddressed/undiagnosed cause fatigue, and this may in my opinion be a potentially much more important cause than direct metabolic effects such as hyperglycemia, or chronic inflammation. If this is the case you’d however expect to see a substantial sex difference, as the autoimmune syndromes are in general much more likely to hit females than males. I’m not completely sure how to interpret a few of the results reported, but to me it doesn’t look like the sex differences in this study are anywhere near ‘large enough’ to support such an explanatory model, though. Another big problem is also that fatigue seems to be more common in young patients, which is weird; most long-term complications display significant (positive) duration dependence, and when diabetes is a component of an autoimmune syndrome diabetes tend to develop first, with other diseases hitting later, usually in middle age. Duration and age are strongly correlated, and a negative duration dependence in a diabetes complication setting is a surprising and unusual finding that needs to be explained, badly; it’s unexpected and may in my opinion be the sign of a poor disease model. It’d make more sense for disease-related fatigue to present late, rather than early, I don’t really know what to make of that negative age gradient. ‘More studies needed’ (preferably by people familiar with those autoimmune syndromes..), etc…

ii. Risk for End-Stage Renal Disease Over 25 Years in the Population-Based WESDR Cohort.

“It is well known that diabetic nephropathy is the leading cause of end-stage renal disease (ESRD) in many regions, including the U.S. (1). Type 1 diabetes accounts for >45,000 cases of ESRD per year (2), and the incidence may be higher than in people with type 2 diabetes (3). Despite this, there are few population-based data available regarding the prevalence and incidence of ESRD in people with type 1 diabetes in the U.S. (4). A declining incidence of ESRD has been suggested by findings of lower incidence with increasing calendar year of diagnosis and in comparison with older reports in some studies in Europe and the U.S. (58). This is consistent with better diabetes management tools becoming available and increased renoprotective efforts, including the greater use of ACE inhibitors and angiotensin type II receptor blockers, over the past two to three decades (9). Conversely, no reduction in the incidence of ESRD across enrollment cohorts was found in a recent clinic-based study (9). Further, an increase in ESRD has been suggested for older but not younger people (9). Recent improvements in diabetes care have been suggested to delay rather than prevent the development of renal disease in people with type 1 diabetes (4).

A decrease in the prevalence of proliferative retinopathy by increasing calendar year of type 1 diabetes diagnosis was previously reported in the Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR) cohort (10); therefore, we sought to determine if a similar pattern of decline in ESRD would be evident over 25 years of follow-up. Further, we investigated factors that may mediate a possible decline in ESRD as well as other factors associated with incident ESRD over time.”

“At baseline, 99% of WESDR cohort members were white and 51% were male. Individuals were 3–79 years of age (mean 29) with diabetes duration of 0–59 years (mean 15), diagnosed between 1922 and 1980. Four percent of individuals used three or more daily insulin injections and none used an insulin pump. Mean HbA1c was 10.1% (87 mmol/mol). Only 16% were using an antihypertensive medication, none was using an ACE inhibitor, and 3% reported a history of renal transplant or dialysis (ESRD). At 25 years, 514 individuals participated (52% of original cohort at baseline, n = 996) and 367 were deceased (37% of baseline). Mean HbA1c was much lower than at baseline (7.5%, 58 mmol/mol), the decline likely due to the improvements in diabetes care, with 80% of participants using intensive insulin management (three or more daily insulin injections or insulin pump). The decline in HbA1c was steady, becoming slightly steeper following the results of the DCCT (25). Overall, at the 25-year follow-up, 47% had proliferative retinopathy, 53% used aspirin daily, and 54% reported taking antihypertensive medications, with the majority (87%) using an ACE inhibitor. Thirteen percent reported a history of ESRD.”

“Prevalence of ESRD was negligible until 15 years of diabetes duration and then steadily increased with 5, 8, 10, 13, and 14% reporting ESRD by 15–19, 20–24, 25–29, 30–34, and 35+ years of diabetes duration, respectively. […] After 15 years of diagnosis, prevalence of ESRD increased with duration in people diagnosed from 1960 to 1980, with the lowest increase in people with the most recent diagnosis. People diagnosed from 1922 to 1959 had consistent rather than increasing levels of ESRD with duration of 20+ years. If not for their greater mortality (at the 25-year follow-up, 48% of the deceased had been diagnosed prior to 1960), an increase with duration may have also been observed.

From baseline, the unadjusted cumulative 25-year incidence of ESRD was 17.9% (95% CI 14.3–21.5) in males, 10.3% (7.4–13.2) in females, and 14.2% (11.9–16.5) overall. For those diagnosed in 1970–1980, the cumulative incidence at 14, 20, and 25 years of follow-up (or ∼15–25, 20–30, and 25–35 years diabetes duration) was 5.2, 7.9, and 9.3%, respectively. At 14, 20, and 25 years of follow-up (or 35, 40, and 45 up to 65+ years diabetes duration), the cumulative incidence in those diagnosed during 1922–1969 was 13.6, 16.3, and 18.8%, respectively, consistent with the greater prevalence observed for these diagnosis periods at longer duration of diabetes.”

“The unadjusted hazard of ESRD was reduced by 70% among those diagnosed in 1970–1980 as compared with those in 1922–1969 (HR 0.29 [95% CI 0.19–0.44]). Duration (by 10%) and HbA1c (by an additional 10%) partially mediated this association […] Blood pressure and antihypertensive medication use each further attenuated the association. When fully adjusted for these and [other risk factors included in the model], period of diagnosis was no longer significant (HR 0.89 [0.55–1.45]). Sensitivity analyses for the hazard of incident ESRD or death due to renal disease showed similar findings […] The most parsimonious model included diabetes duration, HbA1c, age, sex, systolic and diastolic blood pressure, and history of antihypertensive medication […]. A 32% increased risk for incident ESRD was found per increasing year of diabetes duration at 0–15 years (HR 1.32 per year [95% CI 1.16–1.51]). The hazard plateaued (1.01 per year [0.98–1.05]) after 15 years of duration of diabetes. Hazard of ESRD increased with increasing HbA1c (1.28 per 1% or 10.9 mmol/mol increase [1.14–1.45]) and blood pressure (1.51 per 10 mmHg increase in systolic pressure [1.35–1.68]; 1.12 per 5 mmHg increase in diastolic pressure [1.01–1.23]). Use of antihypertensive medications increased the hazard of incident ESRD nearly fivefold [this finding is almost certainly due to confounding by indication, as also noted by the authors later on in the paper – US], and males had approximately two times the risk as compared with females. […] Having proliferative retinopathy was strongly associated with increased risk (HR 5.91 [3.00–11.6]) and attenuated the association between sex and ESRD.”

“The current investigation […] sought to provide much-needed information on the prevalence and incidence of ESRD and associated risk specific to people with type 1 diabetes. Consistent with a few previous studies (5,7,8), we observed decreased prevalence and incidence of ESRD among individuals with type 1 diabetes diagnosed in the 1970s compared with prior to 1970. The Epidemiology of Diabetes Complications (EDC) Study, another large cohort of people with type 1 diabetes followed over a long period of time, reported cumulative incidence rates of 2–6% for those diagnosed after 1970 and with similar duration (7), comparable to our findings. Slightly higher cumulative incidence (7–13%) reported from older studies at slightly lower duration also supports a decrease in incidence of ESRD (2830). Cumulative incidences through 30 years in European cohorts were even lower (3.3% in Sweden [6] and 7.8% in Finland [5]), compared with the 9.3% noted for those diagnosed during 1970–1980 in the WESDR cohort. The lower incidence could be associated with nationally organized care, especially in Sweden where a nationwide intensive diabetes management treatment program was implemented at least a decade earlier than recommendations for intensive care followed from the results of the DCCT in the U.S.”

“We noted an increased risk of incident ESRD in the first 15 years of diabetes not evident at longer durations. This pattern also demonstrated by others could be due to a greater earlier risk among people most genetically susceptible, as only a subset of individuals with type 1 diabetes will develop renal disease (27,28). The risk plateau associated with greater durations of diabetes and lower risk associated with increasing age may also reflect more death at longer durations and older ages. […] Because age and duration are highly correlated, we observed a positive association between age and ESRD only in univariate analyses, without adjustment for duration. The lack of adjustment for diabetes duration may have, in part, explained the increasing incidence of ESRD shown with age for some people in a recent investigation (9). Adjustment for both age and duration was found appropriate after testing for collinearity in the current analysis.”

In conclusion, this U.S. population-based report showed a lower prevalence and incidence of ESRD among those more recently diagnosed, explained by improvements in glycemic and blood pressure control over the last several decades. Even lower rates may be expected for those diagnosed during the current era of diabetes care. Intensive diabetes management, especially for glycemic control, remains important even in long-standing diabetes as potentially delaying the development of ESRD.

iii. Earlier Onset of Complications in Youth With Type 2 Diabetes.

The prevalence of type 2 diabetes in youth is increasing worldwide, coinciding with the rising obesity epidemic (1,2). […] Diabetes is associated with both microvascular and macrovascular complications. The evolution of these complications has been well described in type 1 diabetes (6) and in adult type 2 diabetes (7), wherein significant complications typically manifest 15–20 years after diagnosis (8). Because type 2 diabetes is a relatively new disease in children (first described in the 1980s), long-term outcome data on complications are scant, and risk factors for the development of complications are incompletely understood. The available literature suggests that development of complications in youth with type 2 diabetes may be more rapid than in adults, thus afflicting individuals at the height of their individual and social productivity (9). […] A small but notable proportion of type 2 diabetes is associated with a polymorphism of hepatic nuclear factor (HNF)-1α, a transcription factor expressed in many tissues […] It is not yet known what effect the HNF-1α polymorphism has on the risk of complications associated with diabetes.”

“The main objective of the current study was to describe the time course and risk factors for microvascular complications (nephropathy, retinopathy, and neuropathy) and macrovascular complications (cardiac, cerebrovascular, and peripheral vascular diseases) in a large cohort of youth [diagnosed with type 2 diabetes] who have been carefully followed for >20 years and to compare this evolution with that of youth with type 1 diabetes. We also compared vascular complications in the youth with type 2 diabetes with nondiabetic control youth. Finally, we addressed the impact of HNF-1α G319S on the evolution of complications in young patients with type 2 diabetes.”

“All prevalent cases of type 2 diabetes and type 1 diabetes (control group 1) seen between January 1986 and March 2007 in the DER-CA for youth aged 1–18 years were included. […] The final type 2 diabetes cohort included 342 youth, and the type 1 diabetes control group included 1,011. The no diabetes control cohort comprised 1,710 youth matched to the type 2 diabetes cohort from the repository […] Compared with the youth with type 1 diabetes, the youth with type 2 diabetes were, on average, older at the time of diagnosis and more likely to be female. They were more likely to have a higher BMIz, live in a rural area, have a low SES, and have albuminuria at diagnosis. […] one-half of the type 2 diabetes group was either a heterozygote (GS) or a homozygote (SS) for the HNF-1α polymorphism […] At the time of the last available follow-up in the DER-CA, the youth with diabetes were, on average, between 15 and 16 years of age. […] The median follow-up times in the repository were 4.4 (range 0–27.4) years for youth with type 2 diabetes, 6.7 ( 0–28.2) years for youth with type 1 diabetes, and 6.0 (0–29.9) years for nondiabetic control youth.”

“After controlling for low SES, sex, and BMIz, the risk associated with type 2 versus type 1 diabetes of any complication was an HR of 1.47 (1.02–2.12, P = 0.04). […] In the univariate analysis, youth with type 2 diabetes were at significantly higher risk of developing any vascular (HR 6.15 [4.26–8.87], P < 0.0001), microvascular (6.26 [4.32–9.10], P < 0.0001), or macrovascular (4.44 [1.71–11.52], P < 0.0001) disease compared with control youth without diabetes. In addition, the youth with type 2 diabetes had an increased risk of opthalmologic (19.49 [9.75–39.00], P < 0.0001), renal (16.13 [7.66–33.99], P < 0.0001), and neurologic (2.93 [1.79–4.80], P ≤ 0.001) disease. There were few cardiovascular, cerebrovascular, and peripheral vascular disease events in all groups (five or fewer events per group). Despite this, there was still a statistically significant higher risk of peripheral vascular disease in the type 2 diabetes group (6.25 [1.68–23.28], P = 0.006).”

“Differences in renal and neurologic complications between the two diabetes groups began to occur before 5 years postdiagnosis, whereas differences in ophthalmologic complications began 10 years postdiagnosis. […] Both cardiovascular and cerebrovascular complications were rare in both groups, but peripheral vascular complications began to occur 15 years after diagnosis in the type 2 diabetes group […] The presence of HNF-1α G319S polymorphism in youth with type 2 diabetes was found to be protective of complications. […] Overall, major complications were rare in the type 1 diabetes group, but they occurred in 1.1% of the type 2 diabetes cohort at 10 years, in 26.0% at 15 years, and in 47.9% at 20 years after diagnosis (P < 0.001) […] youth with type 2 diabetes have a higher risk of any complication than youth with type 1 diabetes and nondiabetic control youth. […] The time to both renal and neurologic complications was significantly shorter in youth with type 2 diabetes than in control youth, whereas differences were not significant with respect to opthalmologic and cardiovascular complications between cohorts. […] The current study is consistent with the literature, which has shown high rates of cardiovascular risk factors in youth with type 2 diabetes. However, despite the high prevalence of risk, this study reports low rates of clinical events. Because the median follow-up time was between 5 and 8 years, it is possible that a longer follow-up period would be required to correctly evaluate macrovascular outcomes in young adults. Also possible is that diagnoses of mild disease are not being made because of a low index of suspicion in 20- and 30-year-old patients.”

In conclusion, youth with type 2 diabetes have an increased risk of complications early in the course of their disease. Microvascular complications and cardiovascular risk factors are highly prevalent, whereas macrovascular complications are rare in young adulthood. HbA1c is an important modifiable risk factor; thus, optimizing glycemic control should remain an important goal of therapy.”

iv. HbA1c and Coronary Heart Disease Risk Among Diabetic Patients.

“We prospectively investigated the association of HbA1c at baseline and during follow-up with CHD risk among 17,510 African American and 12,592 white patients with type 2 diabetes. […] During a mean follow-up of 6.0 years, 7,258 incident CHD cases were identified. The multivariable-adjusted hazard ratios of CHD associated with different levels of HbA1c at baseline (<6.0 [reference group], 6.0–6.9, 7.0–7.9, 8.0–8.9, 9.0–9.9, 10.0–10.9, and ≥11.0%) were 1.00, 1.07 (95% CI 0.97–1.18), 1.16 (1.04–1.31), 1.15 (1.01–1.32), 1.26 (1.09–1.45), 1.27 (1.09–1.48), and 1.24 (1.10–1.40) (P trend = 0.002) for African Americans and 1.00, 1.04 (0.94–1.14), 1.15 (1.03–1.28), 1.29 (1.13–1.46), 1.41 (1.22–1.62), 1.34 (1.14–1.57), and 1.44 (1.26–1.65) (P trend <0.001) for white patients, respectively. The graded association of HbA1c during follow-up with CHD risk was observed among both African American and white diabetic patients (all P trend <0.001). Each one percentage increase of HbA1c was associated with a greater increase in CHD risk in white versus African American diabetic patients. When stratified by sex, age, smoking status, use of glucose-lowering agents, and income, this graded association of HbA1c with CHD was still present. […] The current study in a low-income population suggests a graded positive association between HbA1c at baseline and during follow-up with the risk of CHD among both African American and white diabetic patients with low socioeconomic status.”

A few more observations from the conclusions:

“Diabetic patients experience high mortality from cardiovascular causes (2). Observational studies have confirmed the continuous and positive association between glycemic control and the risk of cardiovascular disease among diabetic patients (4,5). But the findings from RCTs are sometimes uncertain. Three large RCTs (79) designed primarily to determine whether targeting different glucose levels can reduce the risk of cardiovascular events in patients with type 2 diabetes failed to confirm the benefit. Several reasons for the inconsistency of these studies can be considered. First, small sample sizes, short follow-up duration, and few CHD cases in some RCTs may limit the statistical power. Second, most epidemiological studies only assess a single baseline measurement of HbA1c with CHD risk, which may produce potential bias. The recent analysis of 10 years of posttrial follow-up of the UKPDS showed continued reductions for myocardial infarction and death from all causes despite an early loss of glycemic differences (10). The scientific evidence from RCTs was not sufficient to generate strong recommendations for clinical practice. Thus, consensus groups (AHA, ACC, and ADA) have provided a conservative endorsement (class IIb recommendation, level of evidence A) for the cardiovascular benefits of glycemic control (11). In the absence of conclusive evidence from RCTs, observational epidemiological studies might provide useful information to clarify the relationship between glycemia and CHD risk. In the current study with 30,102 participants with diabetes and 7,258 incident CHD cases during a mean follow-up of 6.0 years, we found a graded positive association by various HbA1c intervals of clinical relevance or by using HbA1c as a continuous variable at baseline and during follow-up with CHD risk among both African American and white diabetic patients. Each one percentage increase in baseline and follow-up HbA1c was associated with a 2 and 5% increased risk of CHD in African American and 6 and 11% in white diabetic patients. Each one percentage increase of HbA1c was associated with a greater increase in CHD risk in white versus African American diabetic patients.”

v. Blood Viscosity in Subjects With Normoglycemia and Prediabetes.

“Blood viscosity (BV) is the force that counteracts the free sliding of the blood layers within the circulation and depends on the internal cohesion between the molecules and the cells. Abnormally high BV can have several negative effects: the heart is overloaded to pump blood in the vascular bed, and the blood itself, more viscous, can damage the vessel wall. Furthermore, according to Poiseuille’s law (1), BV is inversely related to flow and might therefore reduce the delivery of insulin and glucose to peripheral tissues, leading to insulin resistance or diabetes (25).

It is generally accepted that BV is increased in diabetic patients (68). Although the reasons for this alteration are still under investigation, it is believed that the increase in osmolarity causes increased capillary permeability and, consequently, increased hematocrit and viscosity (9). It has also been suggested that the osmotic diuresis, consequence of hyperglycemia, could contribute to reduce plasma volume and increase hematocrit (10).

Cross-sectional studies have also supported a link between BV, hematocrit, and insulin resistance (1117). Recently, a large prospective study has demonstrated that BV and hematocrit are risk factors for type 2 diabetes. Subjects in the highest quartile of BV were >60% more likely to develop diabetes than their counterparts in the lowest quartile (18). This finding confirms previous observations obtained in smaller or selected populations, in which the association between hemoglobin or hematocrit and occurrence of type 2 diabetes was investigated (1922).

These observations suggest that the elevation in BV may be very early, well before the onset of diabetes, but definite data in subjects with normal glucose or prediabetes are missing. In the current study, we evaluated the relationship between BV and blood glucose in subjects with normal glucose or prediabetes in order to verify whether alterations in viscosity are appreciable in these subjects and at which blood glucose concentration they appear.”

“According to blood glucose levels, participants were divided into three groups: group A, blood glucose <90 mg/dL; group B, blood glucose between 90 and 99 mg/dL; and group C, blood glucose between 100 and 125 mg/dL. […] Hematocrit (P < 0.05) and BV (P between 0.01 and 0.001) were significantly higher in subjects with prediabetes and in those with blood glucose ranging from 90 to 99 mg/dL compared with subjects with blood glucose <90 mg/dL. […] The current study shows, for the first time, a direct relationship between BV and blood glucose in nondiabetic subjects. It also suggests that, even within glucose values ​​considered completely normal, individuals with higher blood glucose levels have increases in BV comparable with those observed in subjects with prediabetes. […] Overall, changes in viscosity in diabetic patients are accepted as common and as a result of the disease. However, the relationship between blood glucose, diabetes, and viscosity may be much more complex. […] the main finding of the study is that BV significantly increases already at high-normal blood glucose levels, independently of other common determinants of hemorheology. Intervention studies are needed to verify whether changes in BV can influence the development of type 2 diabetes.”

vi. Higher Relative Risk for Multiple Sclerosis in a Pediatric and Adolescent Diabetic Population: Analysis From DPV Database.

“Type 1 diabetes and multiple sclerosis (MS) are organ-specific inflammatory diseases, which result from an autoimmune attack against either pancreatic β-cells or the central nervous system; a combined appearance has been described repeatedly (13). For children and adolescents below the age of 21 years, the prevalence of type 1 diabetes in Germany and Austria is ∼19.4 cases per 100,000 population, and for MS it is 7–10 per 100,000 population (46). A Danish cohort study revealed a three times higher risk for the development of MS in patients with type 1 diabetes (7). Further, an Italian study conducted in Sardinia showed a five times higher risk for the development of type 1 diabetes in MS patients (8,9). An American study on female adults in whom diabetes developed before the age of 21 years yielded an up to 20 times higher risk for the development of MS (10).

These findings support the hypothesis of clustering between type 1 diabetes and MS. The pathogenesis behind this association is still unclear, but T-cell cross-reactivity was discussed as well as shared disease associations due to the HLA-DRB1-DQB1 gene loci […] The aim of this study was to evaluate the prevalence of MS in a diabetic population and to look for possible factors related to the co-occurrence of MS in children and adolescents with type 1 diabetes using a large multicenter survey from the Diabetes Patienten Verlaufsdokumentation (DPV) database.”

“We used a large database of pediatric and adolescent type 1 diabetic patients to analyze the RR of MS co-occurrence. The DPV database includes ∼98% of the pediatric diabetic population in Germany and Austria below the age of 21 years. In children and adolescents, the RR for MS in type 1 diabetes was estimated to be three to almost five times higher in comparison with the healthy population.”

November 2, 2017 Posted by | Cardiology, Diabetes, Epidemiology, Genetics, Immunology, Medicine, Nephrology, Statistics, Studies | Leave a comment

A few diabetes papers of interest

i. The Pharmacogenetics of Type 2 Diabetes: A Systematic Review.

“We performed a systematic review to identify which genetic variants predict response to diabetes medications.

RESEARCH DESIGN AND METHODS We performed a search of electronic databases (PubMed, EMBASE, and Cochrane Database) and a manual search to identify original, longitudinal studies of the effect of diabetes medications on incident diabetes, HbA1c, fasting glucose, and postprandial glucose in prediabetes or type 2 diabetes by genetic variation.

RESULTS Of 7,279 citations, we included 34 articles (N = 10,407) evaluating metformin (n = 14), sulfonylureas (n = 4), repaglinide (n = 8), pioglitazone (n = 3), rosiglitazone (n = 4), and acarbose (n = 4). […] Significant medication–gene interactions for glycemic outcomes included 1) metformin and the SLC22A1, SLC22A2, SLC47A1, PRKAB2, PRKAA2, PRKAA1, and STK11 loci; 2) sulfonylureas and the CYP2C9 and TCF7L2 loci; 3) repaglinide and the KCNJ11, SLC30A8, NEUROD1/BETA2, UCP2, and PAX4 loci; 4) pioglitazone and the PPARG2 and PTPRD loci; 5) rosiglitazone and the KCNQ1 and RBP4 loci; and 5) acarbose and the PPARA, HNF4A, LIPC, and PPARGC1A loci. Data were insufficient for meta-analysis.

CONCLUSIONS We found evidence of pharmacogenetic interactions for metformin, sulfonylureas, repaglinide, thiazolidinediones, and acarbose consistent with their pharmacokinetics and pharmacodynamics.”

“In this systematic review, we identified 34 articles on the pharmacogenetics of diabetes medications, with several reporting statistically significant interactions between genetic variants and medications for glycemic outcomes. Most pharmacogenetic interactions were only evaluated in a single study, did not use a control group, and/or did not report enough information to judge internal validity. However, our results do suggest specific, biologically plausible, gene–medication interactions, and we recommend confirmation of the biologically plausible interactions as a priority, including those for drug transporters, metabolizers, and targets of action. […] Given the number of comparisons reported in the included studies and the lack of accounting for multiple comparisons in approximately 53% of studies, many of the reported findings may [however] be false positives.”

ii. Insights Offered by Economic Analyses.

“This issue of Diabetes Care includes three economic analyses. The first describes the incremental costs of diabetes over a lifetime and highlights how interventions to prevent diabetes may reduce lifetime costs (1). The second demonstrates that although an expensive, intensive lifestyle intervention for type 2 diabetes does not reduce adverse cardiovascular outcomes over 10 years, it significantly reduces the costs of non-intervention−related medical care (2). The third demonstrates that although the use of the International Association of the Diabetes and Pregnancy Study Groups (IADPSG) criteria for the screening and diagnosis of gestational diabetes mellitus (GDM) results in a threefold increase in the number of people labeled as having GDM, it reduces the risk of maternal and neonatal adverse health outcomes and reduces costs (3). The first report highlights the enormous potential value of intervening in adults at high risk for type 2 diabetes to prevent its development. The second illustrates the importance of measuring economic outcomes in addition to standard clinical outcomes to fully assess the value of new treatments. The third demonstrates the importance of rigorously weighing the costs of screening and treatment against the costs of health outcomes when evaluating new approaches to care.”

“The costs of diabetes monitoring and treatment accrue as of function of the duration of diabetes, so adults who are younger at diagnosis are more likely to survive to develop the late, expensive complications of diabetes, thus they incur higher lifetime costs attributable to diabetes. Zhuo et al. report that people with diabetes diagnosed at age 40 spend approximately $125,000 more for medical care over their lifetimes than people without diabetes. For people diagnosed with diabetes at age 50, the discounted lifetime excess medical spending is approximately $91,000; for those diagnosed at age 60, it is approximately $54,000; and for those diagnosed at age 65, it is approximately $36,000 (1).

These results are very consistent with results reported by the Diabetes Prevention Program (DPP) Research Group, which assessed the cost-effectiveness of diabetes prevention. […] In the simulated lifetime economic analysis [included in that study] the lifestyle intervention was more cost-effective in younger participants than in older participants (5). By delaying the onset of type 2 diabetes, the lifestyle intervention delayed or prevented the need for diabetes monitoring and treatment, surveillance of diabetic microvascular and neuropathic complications, and treatment of the late, expensive complications and comorbidities of diabetes, including end-stage renal disease and cardiovascular disease (5). Although this finding was controversial at the end of the randomized, controlled clinical trial, all but 1 of 12 economic analyses published by 10 research groups in nine countries have demonstrated that lifestyle intervention for the prevention of type 2 diabetes is very cost-effective, if not cost-saving, compared with a placebo intervention (6).

Empiric, within-trial economic analyses of the DPP have now demonstrated that the incremental costs of the lifestyle intervention are almost entirely offset by reductions in the costs of medical care outside the study, especially the cost of self-monitoring supplies, prescription medications, and outpatient and inpatient care (7). Over 10 years, the DPP intensive lifestyle intervention cost only ∼$13,000 per quality-adjusted life-year gained when the analysis used an intent-to-treat approach (7) and was even more cost-effective when the analysis assessed outcomes and costs among adherent participants (8).”

“The American Diabetes Association has reported that although institutional care (hospital, nursing home, and hospice care) still account for 52% of annual per capita health care expenditures for people with diabetes, outpatient medications and supplies now account for 30% of expenditures (9). Between 2007 and 2012, annual per capita expenditures for inpatient care increased by 2%, while expenditures for medications and supplies increased by 51% (9). As the costs of diabetes medications and supplies continue to increase, it will be even more important to consider cost savings arising from the less frequent use of medications when evaluating the benefits of nonpharmacologic interventions.”

iii. The Lifetime Cost of Diabetes and Its Implications for Diabetes Prevention. (This is the Zhuo et al. paper mentioned above.)

“We aggregated annual medical expenditures from the age of diabetes diagnosis to death to determine lifetime medical expenditure. Annual medical expenditures were estimated by sex, age at diagnosis, and diabetes duration using data from 2006–2009 Medical Expenditure Panel Surveys, which were linked to data from 2005–2008 National Health Interview Surveys. We combined survival data from published studies with the estimated annual expenditures to calculate lifetime spending. We then compared lifetime spending for people with diabetes with that for those without diabetes. Future spending was discounted at 3% annually. […] The discounted excess lifetime medical spending for people with diabetes was $124,600 ($211,400 if not discounted), $91,200 ($135,600), $53,800 ($70,200), and $35,900 ($43,900) when diagnosed with diabetes at ages 40, 50, 60, and 65 years, respectively. Younger age at diagnosis and female sex were associated with higher levels of lifetime excess medical spending attributed to diabetes.

CONCLUSIONS Having diabetes is associated with substantially higher lifetime medical expenditures despite being associated with reduced life expectancy. If prevention costs can be kept sufficiently low, diabetes prevention may lead to a reduction in long-term medical costs.”

The selection criteria employed in this paper are not perfect; they excluded all individuals below the age of 30 “because they likely had type 1 diabetes”, which although true is only ‘mostly true’. Some of those individuals had(/have) type 2, but if you’re evaluating prevention schemes it probably makes sense to error on the side of caution (better to miss some type 2 patients than to include some type 1s), assuming the timing of the intervention is not too important. This gets more complicated if prevention schemes are more likely to have large and persistent effects in young people – however I don’t think that’s the case, as a counterpoint drug adherence studies often seem to find that young people aren’t particularly motivated to adhere to their treatment schedules compared to their older counterparts (who might have more advanced disease and so are more likely to achieve symptomatic relief by adhering to treatments).

A few more observations from the paper:

“The prevalence of participants with diabetes in the study population was 7.4%, of whom 54% were diagnosed between the ages of 45 and 64 years. The mean age at diagnosis was 55 years, and the mean length of time since diagnosis was 9.4 years (39% of participants with diabetes had been diagnosed for ≤5 years, 32% for 6–15 years, and 27% for ≥16 years). […] The observed annual medical spending for people with diabetes was $13,966—more than twice that for people without diabetes.”

“Regardless of diabetes status, the survival-adjusted annual medical spending decreased after age 60 years, primarily because of a decreasing probability of survival. Because the probability of survival decreased more rapidly in people with diabetes than in those without, corresponding spending declined as people died and no longer accrued medical costs. For example, among men diagnosed with diabetes at age 40 years, 34% were expected to survive to age 80 years; among men of the same age who never developed diabetes, 55% were expected to survive to age 80 years. The expected annual expenditure for a person diagnosed with diabetes at age 40 years declined from $8,500 per year at age 40 years to $3,400 at age 80 years, whereas the expenses for a comparable person without diabetes declined from $3,900 to $3,200 over that same interval. […] People diagnosed with diabetes at age 40 years lived with the disease for an average of 34 years after diagnosis. Those diagnosed when older lived fewer years and, therefore, lost fewer years of life. […] The annual excess medical spending attributed to diabetes […] was smaller among people who were diagnosed at older ages. For men diagnosed at age 40 years, annual medical spending was $3,700 higher than that of similar men without diabetes; spending was $2,900 higher for those diagnosed at age 50 years; $2,200 higher for those diagnosed at age 60 years; and $2,000 higher for those diagnosed at age 65 years. Among women diagnosed with diabetes, the excess annual medical spending was consistently higher than for men of the same age at diagnosis.”

“Regardless of age at diagnosis, people with diabetes spent considerably more on health care after age 65 years than their nondiabetic counterparts. Health care spending attributed to diabetes after age 65 years ranged from $23,900 to $40,900, depending on sex and age at diagnosis. […] Of the total excess lifetime medical spending among an average diabetic patient diagnosed at age 50 years, prescription medications and inpatient care accounted for 44% and 35% of costs, respectively. Outpatient care and other medical care accounted for 17% and 4% of costs, respectively.”

“Our findings differed from those of studies of the lifetime costs of other chronic conditions. For instance, smokers have a lower average lifetime medical cost than nonsmokers (29) because of their shorter life spans. Smokers have a life expectancy about 10 years less than those who do not smoke (30); life expectancy is 16 years less for those who develop smoking-induced cancers (31). As a result, smoking cessation leads to increased lifetime spending (32). Studies of the lifetime costs for an obese person relative to a person with normal body weight show mixed results: estimated excess lifetime medical costs for people with obesity range from $3,790 less to $39,000 more than costs for those who are nonobese (33,34). […] obesity, when considered alone, results in much lower annual excess medical costs than diabetes (–$940 to $1,150 for obesity vs. $2,000 to $4,700 for diabetes) when compared with costs for people who are nonobese (33,34).”

iv. Severe Hypoglycemia and Mortality After Cardiovascular Events for Type 1 Diabetic Patients in Sweden.

“This study examines factors associated with all-cause mortality after cardiovascular complications (myocardial infarction [MI] and stroke) in patients with type 1 diabetes. In particular, we aim to determine whether a previous history of severe hypoglycemia is associated with increased mortality after a cardiovascular event in type 1 diabetic patients.

Hypoglycemia is the most common and dangerous acute complication of type 1 diabetes and can be life threatening if not promptly treated (1). The average individual with type 1 diabetes experiences about two episodes of symptomatic hypoglycemia per week, with an annual prevalence of 30–40% for hypoglycemic episodes requiring assistance for recovery (2). We define severe hypoglycemia to be an episode of hypoglycemia that requires hospitalization in this study. […] Patients with type 1 diabetes are more susceptible to hypoglycemia than those with type 2 diabetes, and therefore it is potentially of greater relevance if severe hypoglycemia is associated with mortality (6).”

“This study uses a large linked data set comprising health records from the Swedish National Diabetes Register (NDR), which were linked to administrative records on hospitalization, prescriptions, and national death records. […] [The] study is based on data from four sources: 1) risk factor data from the Swedish NDR […], 2) hospital records of inpatient episodes from the National Inpatients Register (IPR) […], 3) death records […], and 4) prescription data records […]. A study comparing registered diagnoses in the IPR with information in medical records found positive predictive values of IPR diagnoses were 85–95% for most diagnoses (8). In terms of NDR coverage, a recent study found that 91% of those aged 18–34 years and with type 1 diabetes in the Prescribed Drug Register could be matched with those in the NDR for 2007–2009 (9).”

“The outcome of the study was all-cause mortality after a major cardiovascular complication (MI or stroke). Our sample for analysis included patients with type 1 diabetes who visited a clinic after 2002 and experienced a major cardiovascular complication after this clinic visit. […] We define type 1 diabetes as diabetes diagnosed under the age of 30 years, being reported as being treated with insulin only at some clinic visit, and when alive, having had at least one prescription for insulin filled per year between 2006 and 2010 […], and not having filled a prescription for metformin at any point between July 2005 and December 2010 (under the assumption that metformin users were more likely to be type 2 diabetes patients).”

“Explanatory variables included in both models were type of complication (MI or stroke), age at complication, duration of diabetes, sex, smoking status, HbA1c, BMI, systolic blood pressure, diastolic blood pressure, chronic kidney disease status based on estimated glomerular filtration rate, microalbuminuria and macroalbuminuria status, HDL, LDL, total–to–HDL cholesterol ratio, triglycerides, lipid medication status, clinic visits within the year prior to the CVD event, and prior hospitalization events: hypoglycemia, hyperglycemia, MI, stroke, heart failure, AF, amputation, PVD, ESRD, IHD/unstable angina, PCI, and CABG. The last known value for each clinical risk factor, prior to the cardiovascular complication, was used for analysis. […] Initially, all explanatory variables were included and excluded if the variable was not statistically significant at a 5% level (P < 0.05) via stepwise backward elimination.” [Aaaaaaargh! – US. These guys are doing a lot of things right, but this is not one of them. Just to mention this one more time: “Generally, hypothesis testing is a very poor basis for model selection […] There is no statistical theory that supports the notion that hypothesis testing with a fixed α level is a basis for model selection.” (Burnham & Anderson)]

“Patients who had prior hypoglycemic events had an estimated HR for mortality of 1.79 (95% CI 1.37–2.35) in the first 28 days after a CVD event and an estimated HR of 1.25 (95% CI 1.02–1.53) of mortality after 28 days post CVD event in the backward regression model. The univariate analysis showed a similar result compared with the backward regression model, with prior hypoglycemic events having an estimated HR for mortality of 1.79 (95% CI 1.38–2.32) and 1.35 (95% CI 1.11–1.65) in the logistic and Cox regressions, respectively. Even when all explanatory factors were included in the models […], the mortality increase associated with a prior severe hypoglycemic event was still significant, and the P values and SE are similar when compared with the backward stepwise regression. Similarly, when explanatory factors were included individually, the mortality increase associated with a prior severe hypoglycemic event was also still significant.” [Again, this sort of testing scheme is probably not a good approach to getting at a good explanatory model, but it’s what they did – US]

“The 5-year cumulative estimated mortality risk for those without complications after MI and stroke were 40.1% (95% CI 35.2–45.1) and 30.4% (95% CI 26.3–34.6), respectively. Patients with prior heart failure were at the highest estimated 5-year cumulative mortality risk, with those who suffered an MI and stroke having a 56.0% (95% CI 47.5–64.5) and 44.0% (95% CI 35.8–52.2) 5-year cumulative mortality risk, respectively. Patients who had a prior severe hypoglycemic event and suffered an MI had an estimated 5-year cumulative mortality risk at age 60 years of 52.4% (95% CI 45.3–59.5), and those who suffered a stroke had a 5-year cumulative mortality risk of 39.8% (95% CI 33.4–46.3). Patients at age 60 years who suffer a major CVD complication have over twofold risk of 5-year mortality compared with the general type 1 diabetic Swedish population, who had an estimated 5-year mortality risk of 13.8% (95% CI 12.0–16.1).”

“We found evidence that prior severe hypoglycemia is associated with reduced survival after a major CVD event but no evidence that prior severe hypoglycemia is associated with an increased risk of a subsequent CVD event.

Compared with the general type 1 diabetic Swedish population, a major CVD complication increased 5-year mortality risk at age 60 years by >25% and 15% in patients with an MI and stroke, respectively. Patients with a history of a hypoglycemic event had an even higher mortality after a major CVD event, with approximately an additional 10% being dead at the 5-year mark. This risk was comparable with that in those with late-stage kidney disease. This information is useful in determining the prognosis of patients after a major cardiovascular event and highlights the need to include this as a risk factor in simulation models (18) that are used to improve decision making (19).”

“This is the first study that has found some evidence of a dose-response relationship, where patients who experienced two or more severe hypoglycemic events had higher mortality after a cardiovascular event compared with those who experienced one severe hypoglycemic event. A lack of statistical power prevented us from investigating this further when we tried to stratify by number of prior severe hypoglycemic events in our regression models. There was no evidence of a dose-response relationship between repeated episodes of severe hypoglycemia and vascular outcomes or death in previous type 2 diabetes studies (5).”

v. Alterations in White Matter Structure in Young Children With Type 1 Diabetes.

“Careful regulation of insulin dosing, dietary intake, and activity levels are essential for optimal glycemic control in individuals with type 1 diabetes. However, even with optimal treatment many children with type 1 diabetes have blood glucose levels in the hyperglycemic range for more than half the day and in the hypoglycemic range for an hour or more each day (1). Brain cells may be especially sensitive to aberrant blood glucose levels, as glucose is the brain’s principal substrate for its energy needs.

Research in animal models has shown that white matter (WM) may be especially sensitive to dysglycemia-associated insult in diabetes (24). […] Early childhood is a period of rapid myelination and brain development (6) and of increased sensitivity to insults affecting the brain (6,7). Hence, study of the developing brain is particularly important in type 1 diabetes.”

“WM structure can be measured with diffusion tensor imaging (DTI), a method based on magnetic resonance imaging (MRI) that uses the movement of water molecules to characterize WM brain structure (8,9). Results are commonly reported in terms of mathematical scalars (representing vectors in vector space) such as fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD). FA reflects the degree of diffusion anisotropy of water (how diffusion varies along the three axes) within a voxel (three-dimensional pixel) and is determined by fiber diameter and density, myelination, and intravoxel fiber-tract coherence (increases in which would increase FA), as well as extracellular diffusion and interaxonal spacing (increases in which would decrease FA) (10). AD, a measure of water diffusivity along the main axis of diffusion within a voxel, is thought to reflect fiber coherence and structure of axonal membranes (increases in which would increase AD), as well as microtubules, neurofilaments, and axonal branching (increases in which would decrease AD) (11,12). RD, the mean of the diffusivities perpendicular to the vector with the largest eigenvalue, is thought to represent degree of myelination (13,14) (more myelin would decrease RD values) and axonal “leakiness” (which would increase RD). Often, however, a combination of these WM characteristics results in opposing contributions to the final observed FA/AD/RD value, and thus DTI scalars should not be interpreted globally as “good” or “bad” (15). Rather, these scalars can show between-group differences and relationships between WM structure and clinical variables and are suggestive of underlying histology. Definitive conclusions about histology of WM can only be derived from direct microscopic examination of biological tissue.”

“Children (ages 4 to <10 years) with type 1 diabetes (n = 127) and age-matched nondiabetic control subjects (n = 67) had diffusion weighted magnetic resonance imaging scans in this multisite neuroimaging study. Participants with type 1 diabetes were assessed for HbA1c history and lifetime adverse events, and glucose levels were monitored using a continuous glucose monitor (CGM) device and standardized measures of cognition.

RESULTS Between-group analysis showed that children with type 1 diabetes had significantly reduced axial diffusivity (AD) in widespread brain regions compared with control subjects. Within the type 1 diabetes group, earlier onset of diabetes was associated with increased radial diffusivity (RD) and longer duration was associated with reduced AD, reduced RD, and increased fractional anisotropy (FA). In addition, HbA1c values were significantly negatively associated with FA values and were positively associated with RD values in widespread brain regions. Significant associations of AD, RD, and FA were found for CGM measures of hyperglycemia and glucose variability but not for hypoglycemia. Finally, we observed a significant association between WM structure and cognitive ability in children with type 1 diabetes but not in control subjects. […] These results suggest vulnerability of the developing brain in young children to effects of type 1 diabetes associated with chronic hyperglycemia and glucose variability.”

“The profile of reduced overall AD in type 1 diabetes observed here suggests possible axonal damage associated with diabetes (30). Reduced AD was associated with duration of type 1 diabetes suggesting that longer exposure to diabetes worsens the insult to WM structure. However, measures of hyperglycemia and glucose variability were either not associated or were positively associated with AD values, suggesting that these measures did not contribute to the observed decreased AD in the type 1 diabetes group. A possible explanation for these observations is that several biological processes influence WM structure in type 1 diabetes. Some processes may be related to insulin insufficiency or C-peptide levels independent of glucose levels (31,32) and may affect WM coherence (and reduce AD values as observed in the between-group results). Other processes related to hyperglycemia and glucose variability may target myelin (resulting in reduced FA and increased RD) as well as reduced axonal branching (both would result in increased AD values). Alternatively, these seemingly conflicting AD observations may be due to a dominant effect of age, which could overshadow effects from dysglycemia.

Early age of onset is one of the most replicable risk factors for cognitive impairments in type 1 diabetes (33,34). It has been hypothesized that young children are especially vulnerable to brain insults resulting from episodes of chronic hyperglycemia, hypoglycemia, and acute hypoglycemic complications of type 1 diabetes (seizures and severe hypoglycemic episodes). In addition, fear of hypoglycemia often results in caregivers maintaining relatively higher blood glucose to avoid lows altogether (1), especially in very young children. However, our study suggests that this approach of aggressive hypoglycemia avoidance resulting in hyperglycemia may not be optimal and may be detrimental to WM structure in young children.

Neuronal damage (reflected in altered WM structure) may affect neuronal signal transfer and, thus, cognition (35). Cognitive domains commonly reported to be affected in children with type 1 diabetes include general intellectual ability, visuospatial abilities, attention, memory, processing speed, and executive function (3638). In our sample, even though the duration of illness was relatively short (2.9 years on average), there were modest but significant cognitive differences between children with type 1 diabetes and control subjects (24).”

“In summary, we present results from the largest study to date investigating WM structure in very young children with type 1 diabetes. We observed significant and widespread brain differences in the WM microstructure of children with type 1 diabetes compared with nondiabetic control subjects and significant associations between WM structure and measures of hyperglycemia, glucose variability, and cognitive ability in the type 1 diabetic population.”

vi. Ultrasound Findings After Surgical Decompression of the Tarsal Tunnel in Patients With Painful Diabetic Polyneuropathy: A Prospective Randomized Study.

“Polyneuropathy is a common complication in diabetes. The prevalence of neuropathy in patients with diabetes is ∼30%. During the course of the disease, up to 50% of the patients will eventually develop neuropathy (1). Its clinical features are characterized by numbness, tingling, or burning sensations and typically extend in a distinct stocking and glove pattern. Prevention plays a key role since poor glucose control is a major risk factor in the development of diabetic polyneuropathy (DPN) (1,2).

There is no clear definition for the onset of painful diabetic neuropathy. Different hypotheses have been formulated.

Hyperglycemia in diabetes can lead to osmotic swelling of the nerves, related to increased glucose conversion into sorbitol by the enzyme aldose reductase (2,3). High sorbitol concentrations might also directly cause axonal degeneration and demyelination (2). Furthermore, stiffening and thickening of ligamental structures and the plantar fascia make underlying structures more prone to biomechanical compression (46). A thicker and stiffer retinaculum might restrict movements and lead to alterations of the nerve in the tarsal tunnel.

Both swelling of the nerve and changes in the tarsal tunnel might lead to nerve damage through compression.

Furthermore, vascular changes may diminish endoneural blood flow and oxygen distribution. Decreased blood supply in the (compressed) nerve might lead to ischemic damage as well as impaired nerve regeneration.

Several studies suggest that surgical decompression of nerves at narrow anatomic sites, e.g., the tarsal tunnel, is beneficial and has a positive effect on pain, sensitivity, balance, long-term risk of ulcers and amputations, and quality of life (3,710). Since the effect of decompression of the tibial nerve in patients with DPN has not been proven with a randomized clinical trial, its contribution as treatment for patients with painful DPN is still controversial. […] In this study, we compare the mean CSA and any changes in shape of the tibial nerve before and after decompression of the tarsal tunnel using ultrasound in order to test the hypothesis that the tarsal tunnel leads to compression of the tibial nerve in patients with DPN.”

“This study, with a large sample size and standardized sonographic imaging procedure with a good reliability, is the first randomized controlled trial that evaluates the effect of decompression of the tibial nerve on the CSA. Although no effect on CSA after surgery was found, this study using ultrasound demonstrates a larger and swollen tibial nerve and thicker flexor retinaculum at the ankle in patients with DPN compared with healthy control subjects.”

I would have been interested to know if there were any observable changes in symptom relief measures post-surgery, even if such variables are less ‘objective’ than measures like CSA (less objective, but perhaps more relevant to the patient…), but the authors did not look at those kinds of variables.

vii. Nonalcoholic Fatty Liver Disease Is Independently Associated With an Increased Incidence of Chronic Kidney Disease in Patients With Type 1 Diabetes.

“Nonalcoholic fatty liver disease (NAFLD) has reached epidemic proportions worldwide (1). Up to 30% of adults in the U.S. and Europe have NAFLD, and the prevalence of this disease is much higher in people with diabetes (1,2). Indeed, the prevalence of NAFLD on ultrasonography ranges from ∼50 to 70% in patients with type 2 diabetes (35) and ∼40 to 50% in patients with type 1 diabetes (6,7). Notably, patients with diabetes and NAFLD are also more likely to develop more advanced forms of NAFLD that may result in end-stage liver disease (8). However, accumulating evidence indicates that NAFLD is associated not only with liver-related morbidity and mortality but also with an increased risk of developing cardiovascular disease (CVD) and other serious extrahepatic complications (810).”

“Increasing evidence indicates that NAFLD is strongly associated with an increased risk of CKD [chronic kidney disease, US] in people with and without diabetes (11). Indeed, we have previously shown that NAFLD is associated with an increased prevalence of CKD in patients with both type 1 and type 2 diabetes (1517), and that NAFLD independently predicts the development of incident CKD in patients with type 2 diabetes (18). However, many of the risk factors for CKD are different in patients with type 1 and type 2 diabetes, and to date, it is uncertain whether NAFLD is an independent risk factor for incident CKD in type 1 diabetes or whether measurement of NAFLD improves risk prediction for CKD, taking account of traditional risk factors for CKD.

Therefore, the aim of the current study was to investigate 1) whether NAFLD is associated with an increased incidence of CKD and 2) whether measurement of NAFLD improves risk prediction for CKD, adjusting for traditional risk factors, in type 1 diabetic patients.”

“Using a retrospective, longitudinal cohort study design, we have initially identified from our electronic database all Caucasian type 1 diabetic outpatients with preserved kidney function (i.e., estimated glomerular filtration rate [eGFR] ≥60 mL/min/1.73 m2) and with no macroalbuminuria (n = 563), who regularly attended our adult diabetes clinic between 1999 and 2001. Type 1 diabetes was diagnosed by the typical presentation of disease, the absolute dependence on insulin treatment for survival, the presence of undetectable fasting C-peptide concentrations, and the presence of anti–islet cell autoantibodies. […] Overall, 261 type 1 diabetic outpatients were included in the final analysis and were tested for the development of incident CKD during the follow-up period […] All participants were periodically seen (every 3–6 months) for routine medical examinations of glycemic control and chronic complications of diabetes. No participants were lost to follow-up. […] For this study, the development of incident CKD was defined as occurrence of eGFR <60 mL/min/1.73 m2 and/or macroalbuminuria (21). Both of these outcome measures were confirmed in all participants in a least two consecutive occasions (within 3–6 months after the first examination).”

“At baseline, the mean eGFRMDRD was 92 ± 23 mL/min/1.73 m2 (median 87.9 [IQR 74–104]), or eGFREPI was 98.6 ± 19 mL/min/1.73 m2 (median 99.7 [84–112]). Most patients (n = 234; 89.7%) had normal albuminuria, whereas 27 patients (10.3%) had microalbuminuria. NAFLD was present in 131 patients (50.2%). […] At baseline, patients who developed CKD at follow-up were older, more likely to be female and obese, and had a longer duration of diabetes than those who did not. These patients also had higher values of systolic blood pressure, A1C, triglycerides, serum GGT, and urinary ACR and lower values of eGFRMDRD and eGFREPI. Moreover, there was a higher percentage of patients with hypertension, metabolic syndrome, microalbuminuria, and some degree of diabetic retinopathy in patients who developed CKD at follow-up compared with those remaining free from CKD. The proportion using antihypertensive drugs (that always included the use of ACE inhibitors or angiotensin receptor blockers) was higher in those who progressed to CKD. Notably, […] this patient group also had a substantially higher frequency of NAFLD on ultrasonography.”

“During follow-up (mean duration 5.2 ± 1.7 years, range 2–10), 61 patients developed CKD using the MDRD study equation to estimate eGFR (i.e., ∼4.5% of participants progressed every year to eGFR <60 mL/min/1.73 m2 or macroalbuminuria). Of these, 28 developed an eGFRMDRD <60 mL/min/1.73 m2 with abnormal albuminuria (micro- or macroalbuminuria), 21 developed a reduced eGFRMDRD with normal albuminuria (but 9 of them had some degree of diabetic retinopathy at baseline), and 12 developed macroalbuminuria alone. None of them developed kidney failure requiring chronic dialysis. […] The annual eGFRMDRD decline for the whole cohort was 2.68 ± 3.5 mL/min/1.73 m2 per year. […] NAFLD patients had a greater annual decline in eGFRMDRD than those without NAFLD at baseline (3.28 ± 3.8 vs. 2.10 ± 3.0 mL/min/1.73 m2 per year, P < 0.005). Similarly, the frequency of a renal functional decline (arbitrarily defined as ≥25% loss of baseline eGFRMDRD) was greater among those with NAFLD than among those without the disease (26 vs. 11%, P = 0.005). […] Interestingly, BMI was not significantly associated with CKD.”

“Our novel findings indicate that NAFLD is strongly associated with an increased incidence of CKD during a mean follow-up of 5 years and that measurement of NAFLD improves risk prediction for CKD, independently of traditional risk factors (age, sex, diabetes duration, A1C, hypertension, baseline eGFR, and microalbuminuria [i.e., the last two factors being the strongest known risk factors for CKD]), in type 1 diabetic adults. Additionally, although NAFLD was strongly associated with obesity, obesity (or increased BMI) did not explain the association between NAFLD and CKD. […] The annual cumulative incidence rate of CKD in our cohort of patients (i.e., ∼4.5% per year) was essentially comparable to that previously described in other European populations with type 1 diabetes and similar baseline characteristics (∼2.5–9% of patients who progressed every year to CKD) (25,26). In line with previously published information (2528), we also found that hypertension, microalbuminuria, and lower eGFR at baseline were strong predictors of incident CKD in type 1 diabetic patients.”

“There is a pressing and unmet need to determine whether NAFLD is associated with a higher risk of CKD in people with type 1 diabetes. It has only recently been recognized that NAFLD represents an important burden of disease for type 2 diabetic patients (11,17,18), but the magnitude of the problem of NAFLD and its association with risk of CKD in type 1 diabetes is presently poorly recognized. Although there is clear evidence that NAFLD is closely associated with a higher prevalence of CKD both in those without diabetes (11) and in those with type 1 and type 2 diabetes (1517), only four prospective studies have examined the association between NAFLD and risk of incident CKD (18,2931), and only one of these studies was published in patients with type 2 diabetes (18). […] The underlying mechanisms responsible for the observed association between NAFLD and CKD are not well understood. […] The possible clinical implication for these findings is that type 1 diabetic patients with NAFLD may benefit from more intensive surveillance or early treatment interventions to decrease the risk for CKD. Currently, there is no approved treatment for NAFLD. However, NAFLD and CKD share numerous cardiometabolic risk factors, and treatment strategies for NAFLD and CKD should be similar and aimed primarily at modifying the associated cardiometabolic risk factors.”

 

October 25, 2017 Posted by | Cardiology, Diabetes, Epidemiology, Genetics, Health Economics, Medicine, Nephrology, Neurology, Pharmacology, Statistics, Studies | Leave a comment