A few diabetes papers of interest

i. Burden of Diabetic Foot Ulcers for Medicare and Private Insurers.

Some observations from the paper (my bold):

According to the American Diabetes Association, the annual cost of diabetes, which affects 22.3 million people in the U.S., was $245 billion in 2012: $176 billion in excess health care expenditures and $69 billion in reduced workforce productivity (1). While much of the excess health care cost is attributable to treatment of diabetes itself, a substantial amount of the cost differential arises via treatment of chronic complications such as those related to the heart, kidneys, and nervous system (1).

One common complication of diabetes is the development of foot ulcers. Historically, foot ulcers have been estimated to affect 1–4% of patients with diabetes annually (2,3) and as many as 25% of the patients with diabetes over their lifetimes (2). More recently, Margolis et al. (3) have estimated that the annual incidence of foot ulcers among patients with diabetes may be as high as 6%. Treatment of diabetic foot ulcers (DFUs) includes conventional wound management (e.g., debridement, moist dressings, and offloading areas of high pressure or friction) as well as more sophisticated treatments such as bioengineered cellular technologies and hyperbaric oxygen therapy (HBO) (4).

DFUs often require extensive healing time and are associated with increased risk for infections and other sequelae that can result in severe and costly outcomes (4). […] DFU patients have a low survival prognosis, with a 3-year cumulative mortality rate of 28% (6) and rates among amputated patients approaching 50% (7).”

“While DFU patients can require substantial amounts of resource use, little is known about the burden of DFUs imposed on the U.S. health care system and payers. In fact, we are aware of only two studies to date that have estimated the incremental medical resource use and costs of DFU beyond that of diabetes alone (6,8). Neither of these analyses, however, accounted for the many underlying differences between DFU and non-DFU patient populations, such as disproportionate presence of costly underlying comorbid conditions among DFU patients […] Other existing literature on the burden of DFUs in the U.S. calculated the overall health care costs (as opposed to incremental) without reference to a non-DFU control population (911). As a result of the variety of data and methodologies used, it is not surprising that the burden of DFUs reported in the literature is wide-ranging, with the average per-patient costs, for example, ranging from $4,595 per episode (9) to over $35,000 annually for all services (6).

The objective of this study was to expand and improve on previous research to provide a more robust, current estimate of incremental clinical and economic burden of DFUs. To do so, this analysis examined the differences in medical resource use and costs between patients with DFUs during a recent time period (January 2007–September 2011) and a matched control population with diabetes but without DFUs, using administrative claims records from nationally representative databases for Medicare and privately insured populations. […] [Our] criteria resulted in a final analytic sample of 231,438 Medicare patients, with 29,681 (12.8%) identified as DFU patients and the remaining 201,757 comprising the potential control population of non-DFU diabetic patients. For private insurance, 119,018 patients met the sample selection criteria, with 5,681 (4.8%) DFU patients and 113,337 potential controls (Fig. 1).”

Prior to matching, DFU patients were statistically different from the non-DFU control population on nearly every dimension examined during the 12-month preindex period. […] The matching process resulted in the identification of 27,878 pairs of DFU and control patients for Medicare and 4,536 pairs for private insurance that were very similar with regards to preindex patient characteristics […] [I]mportantly, the matched DFU and control groups had comparable health care costs during the 12 months prior to the index date (Medicare, $17,744 DFU and controls; private insurance, $14,761 DFU vs. $14,766 controls). […] Despite having matched the groups to ensure similar patient characteristics, DFU patients used significantly (P < 0.0001) more medical resources during the 12-month follow-up period than did the matched controls […]. Among matched Medicare patients, DFU patients had 138.2% more days hospitalized, 85.4% more days of home health care, 40.6% more ED visits, and 35.1% more outpatient/physician office visits. The results were similar for the privately insured DFU patients, who had 173.5% more days hospitalized, 230.0% more days of home health care, 109.0% more ED visits, and 42.5% more outpatient/physician office visits than matched controls. […] The rate of lower limb amputations was 3.8% among matched Medicare DFU patients and 5.0% among matched privately insured DFU patients. In contrast, observed lower limb amputation rates among diabetic patients without foot ulcer were only 0.04% in Medicare and 0.02% in private insurance.”

Increased medical resource utilization resulted in DFU patients having approximately twice the costs as the matched non-DFU controls […], with annual incremental per-patient medical costs ranging from $11,710 for Medicare ($28,031 vs. $16,320; P < 0.0001) to $15,890 for private insurance ($26,881 vs. $10,991; P < 0.0001). All places of service (i.e., inpatient, ED, outpatient/physician office, home health care, and other) contributed approximately equally to the cost differential among Medicare patients. For the privately insured, however, increased inpatient costs ($17,061 vs. $6,501; P < 0.0001) were responsible for nearly two-thirds of the overall cost differential, […] resulting in total incremental direct health care (i.e., medical + prescription drug) costs of $16,883 ($31,419 vs. $14,536; P < 0.0001). Substantial proportions of the incremental medical costs were attributable to claims with DFU-related diagnoses or procedures for both Medicare (45.1%) and privately insured samples (60.3%).”

“Of the 4,536 matched pairs of privately insured patients, work-loss information was available for 575 DFU patients and 857 controls. DFU patients had $3,259 in excess work-loss costs ($6,311 vs. $3,052; P < 0.0001) compared with matched controls, with disability and absenteeism comprising $1,670 and $1,589 of the overall differential, respectively […] The results indicate that compared with diabetic patients without foot ulcers, DFU patients miss more days of work due to medical-related absenteeism and to disability, imposing additional burden on employers.”

“These estimates indicate that DFU imposes substantial burden on payers beyond that required to treat diabetes itself. For example, prior research has estimated annual per-patient incremental health care expenditures for patients with diabetes (versus those without diabetes) of approximately $7,900 (1). The estimates of this analysis suggest that the presence of DFU further compounds these incremental treatment costs by adding $11,710 to $16,883 per patient. Stated differently, the results indicate that the excess health care costs of DFU are approximately twice that attributable to treatment of diabetes itself, and that the presence of DFU approximately triples the excess cost differential versus a population of patients without diabetes.

“Using estimates of the total U.S. diabetes population (22.3 million) (1) and the midpoint (3.5%) of annual DFU incidence estimates (1–6%) (2,3), the results of this analysis suggest an annual incremental payer burden of DFU ranging from $9.1 billion (22.3 million patients with diabetes × 3.5% DFU incidence × $11,710 Medicare cost differential) to $13.2 billion (22.3 million patients with diabetes × 3.5% DFU incidence × $16,883 private insurance cost differential). These estimates, moreover, likely understate the actual burden of DFU because the incremental costs referenced in this calculation do not include excess work-loss costs described above, prescription drug costs for Medicare patients, out-of-pocket costs paid by the patient, costs borne by supplemental insurers, and other (non-work loss) indirect costs such as those associated with premature mortality, reduced quality of life, and informal caregiving.”

ii. Contributors to Mortality in High-Risk Diabetic Patients in the Diabetes Heart Study.

“Rates of cardiovascular disease (CVD) are two- to fourfold greater in individuals with type 2 diabetes compared with nondiabetic individuals, and up to 65% of all-cause mortality among individuals with type 2 diabetes is attributed to CVD (1,2). However, the risk profile is not uniform for all individuals affected by diabetes (35). Coronary artery calcified plaque (CAC), determined using computed tomography, is a measure of CVD burden (6,7). CAC scores have been shown to be an independent predictor of CVD outcomes and mortality in population-based studies (810) and a powerful predictor of all-cause and CVD mortality in individuals affected by type 2 diabetes (4,1115).

In the Diabetes Heart Study (DHS), individuals with CAC >1,000 were found to have greater than 6-fold (16) and 11-fold (17) increased risk for all-cause mortality and CVD mortality, respectively, after 7 years of follow-up. With this high risk for adverse outcomes, it is noteworthy that >50% of the DHS sample with CAC >1,000 have lived with this CVD burden for (now) an average of over 12 years. This suggests that outcomes vary in the type 2 diabetic patient population, even among individuals with the highest risk. This study examined the subset of DHS participants with CAC >1,000 and evaluated whether differences in a range of clinical factors and measurements, including modifiable CVD risk factors, provided further insights into risk for mortality.”

“This investigation focused on 371 high-risk participants (from 260 families) […] The goal of this analysis was to identify clinical and other characteristics that influence risk for all-cause mortality in high-risk (baseline CAC >1,000) DHS participants. […] a predominance of traditional CVD risk factors, including older age, male sex, elevated BMI, and high rates of dyslipidemia and hypertension, was evident in this high-risk subgroup (Table 1). These participants were followed for 8.2 ± 3.0 years (mean ± SD), over which time 41% died. […] a number of indices continued to significantly predict outcome following adjustment for other CVD risk factors (including age, sex, and medication use) […]. Higher cholesterol and LDL concentrations were associated with an increased risk (∼1.3-fold) for mortality […] Slightly larger increases in risk for mortality were observed with changes in kidney function (1.3- to 1.4-fold) and elevated CRP (∼1.4-fold) […] use of cholesterol-lowering medication was less common among the deceased participants; those reporting no use of cholesterol-lowering medication at baseline were at a 1.4-fold increased risk of mortality […] these results confirm that, even among this high-risk group, heterogeneity in known CVD risk factors and associations with adverse outcomes are still observed and support their ongoing consideration as useful tools for individual risk assessment. Finally, the data presented here suggest that use of cholesterol-lowering medication was strongly associated with protection, supporting the known beneficial effects of cholesterol management on CVD risk (28,29). […] data suggest that cholesterol-lowering medications may be used less than recommended and need to be more aggressively targeted as a critical modifiable risk factor.”

iii. Neurological Consequences of Diabetic Ketoacidosis at Initial Presentation of Type 1 Diabetes in a Prospective Cohort Study of Children.

“Patients aged 6–18 years with and without DKA at diagnosis were studied at four time points: <48 h, 5 days, 28 days, and 6 months postdiagnosis. Patients underwent magnetic resonance imaging (MRI) and spectroscopy with cognitive assessment at each time point. Relationships between clinical characteristics at presentation and MRI and neurologic outcomes were examined using multiple linear regression, repeated-measures, and ANCOVA analyses.”

“With DKA, cerebral white matter showed the greatest alterations with increased total white matter volume and higher mean diffusivity in the frontal, temporal, and parietal white matter. Total white matter volume decreased over the first 6 months. For gray matter in DKA patients, total volume was lower at baseline and increased over 6 months. […] Of note, although changes in total and regional brain volumes over the first 5 days resolved, they were associated with poorer delayed memory recall and poorer sustained and divided attention at 6 months. Age at time of presentation and pH level were predictors of neuroimaging and functional outcomes.

CONCLUSIONS DKA at type 1 diabetes diagnosis results in morphologic and functional brain changes. These changes are associated with adverse neurocognitive outcomes in the medium term.”

“This study highlights the common nature of transient focal cerebral edema and associated impaired mental state at presentation with new-onset type 1 diabetes in children. We demonstrate that alterations occur most markedly in cerebral white matter, particularly in the frontal lobes, and are most prominent in the youngest children with the most dramatic acidemia. […] early brain changes were associated with persisting alterations in attention and memory 6 months later. Children with DKA did not differ in age, sex, SES, premorbid need for school assistance/remediation, or postdiagnosis clinical trajectory. Earlier diagnosis of type 1 diabetes in children may avoid the complication of DKA and the neurological consequences documented in this study and is worthy of a major public health initiative.”

“In relation to clinical risk factors, the degree of acidosis and younger age appeared to be the greatest risk factors for alterations in cerebral structure. […] cerebral volume changes in the frontal, temporal, and parietal regions in the first week after diagnosis were associated with lower attention and memory scores 6 months later, suggesting that functional information processing difficulties persist after resolution of tissue water increases in cerebral white matter. These findings have not been reported to date but are consistent with the growing concern over academic performance in children with diabetes (2). […] Brain injury should no longer be considered a rare complication of DKA. This study has shown that it is both frequent and persistent.” (my bold)

iv. Antihypertensive Treatment and Resistant Hypertension in Patients With Type 1 Diabetes by Stages of Diabetic Nephropathy.

“High blood pressure (BP) is a risk factor for coronary artery disease, heart failure, and stroke, as well as for chronic kidney disease. Furthermore, hypertension has been estimated to affect ∼30% of patients with type 1 diabetes (1,2) and both parallels and precedes the worsening of kidney disease in these patients (35). […] Despite strong evidence that intensive treatment of elevated BP reduces the risk of cardiovascular disease and microvascular complications, as well as improves the prognosis of patients with diabetic nephropathy (especially with the use of ACE inhibitors [ACEIs] and angiotensin II antagonists [angiotensin receptor blockers, ARBs]) (1,911), treatment targets and recommendations seem difficult to meet in clinical practice (1215). This suggests that the patients might either show poor adherence to the treatment and lifestyle changes or have a suboptimal drug regimen. It is evident that most patients with hypertension might require multiple-drug therapy to reach treatment goals (16). However, certain subgroups of the patients have been considered to have resistant hypertension (RH). RH is defined as office BP that remains above target even after using a minimum of three antihypertensive drugs at maximal tolerated doses, from different classes, one of which is a diuretic. Also, patients with controlled BP using four or more antihypertensive drugs are considered resistant to treatment (17).”

“The true prevalence of RH is unknown, but clinical trials suggest a share between 10 and 30% of the hypertensive patients in the general population (18). […] Only a few studies have considered BP control and treatment in patients with type 1 diabetes (2,15,22). Typically these studies have been limited to a small number of participants, which has not allowed stratifying of the patients according to the nephropathy status. The rate of RH is therefore unknown in patients with type 1 diabetes in general and with respect to different stages of diabetic nephropathy. Therefore, we estimated to what extent patients with type 1 diabetes meet the BP targets proposed by the ADA guidelines. We also evaluated the use of antihypertensive medication and the prevalence of RH in the patients stratified by stage of diabetic nephropathy.”

“[A]ll adult patients with type 1 diabetes from >80 hospitals and primary healthcare centers across Finland were asked to participate. Type 1 diabetes was defined by age at onset of diabetes <40 years, C-peptide ≤0.3 nmol/L, and insulin treatment initiated within 1 year of diagnosis, if C-peptide was not measured. […] we used two different ADA BP targets: <130/85 mmHg, which was the target until 2000 (6), and <130/80 mmHg, which was the target between 2001 and 2012 (7). Patients were divided into groups based on whether their BP had reached the target or not and whether the antihypertensive drug was in use or not. […] uncontrolled hypertension was defined as failure to achieve target BP, based on these two different ADA guidelines, despite use of antihypertensive medication. RH was defined as failure to achieve the goal BP (<130/85 mmHg) even after using a minimum of three antihypertensive drugs, from different classes, one of which was a diuretic. […] On the basis of eGFR (mL/min/1.73 m2) level, patients were classified into five groups according to the Kidney Disease Outcomes Quality Initiative (KDOQI) guidelines: stage 1 eGFR ≥90, stage 2 eGFR 60–89, stage 3 eGFR 30–59, stage 4 eGFR 15–29, and stage 5 eGFR <15. Patients who were on dialysis were classified into stage 5. […] A total of 3,678 patients with complete data on systolic and diastolic BP and nephropathy status were identified from the FinnDiane database. […] The mean age was 38.0 ± 12.0 and mean duration of diabetes 22.1 ± 12.3 years.  […] The patients with advanced diabetic nephropathy had higher BP, worse dyslipidemia, poorer glycemic control, and more insulin resistance and macrovascular complications. BMI values were lower in the dialysis patients, probably due to renal cachexia.”

“Of all patients, 60.9% did not reach the BP target <130/85 mmHg, and the proportion was 70.3% with the target of <130/80 mmHg. […] The patients who were not on target had higher age and longer duration of diabetes and were more likely to be men. They also had poorer glycemic and lipid control as well as more micro- and macrovascular complications. […] Based on the BP target <130/85 mmHg, more than half of the patients in the normoalbuminuria group did not reach the BP target, and the share increased along with the worsening of nephropathy; two-thirds of the patients in the microalbuminuria group and fourfifths in the macroalbuminuria group were not on target, while even 90% of the dialysis and kidney transplant patients did not reach the target (Fig. 1A). Based on the stricter BP target of <130/80 mmHg, the numbers were obviously worse, but the trend was the same (Fig. 1B).”

“About 37% of the FinnDiane patients had antihypertensive treatment […] Whereas 14.1% of the patients with normal AER [Albumin Excretion Rate] had antihypertensive treatment, the proportions were 60.5% in the microalbuminuric, 90.3% in the macroalbuminuric, 88.6% in the dialysis, and 91.2% in the kidney transplant patients. However, in all groups, only a minority of the patients had BP values on target with the antihypertensive drug treatment they were prescribed […] The mean numbers of antihypertensive drugs varied within the nephropathy groups between those who had BP on target and those who did not […]. However, only in the micro- (P = 0.02) and macroalbuminuria (P = 0.003) groups were the mean numbers of the drugs higher if the BP was not on target, compared with those who had reached the targets. Notably, among the patients with normoalbuminuria who had not reached the BP target, 58% and, of the patients with microalbuminuria, 61% were taking only one antihypertensive drug. In contrast, more than half of the dialysis and 40% of the macroalbuminuric and transplanted patients, who had not reached the targets, had at least three drugs in their regimen. Moreover, one-fifth of the dialysis, 15% of the macroalbuminuric, and 10% of the transplanted patients had at least four antihypertensive drugs in use without reaching the target (Table 2). Almost all patients treated with antihypertensive drugs in the normo-, micro-, and macroalbuminuria groups (76% of normo-, 93% of micro-, and 89% of macrolbuminuric patients) had ACEIs or ARBs in the regimen. The proportions were lower in the ESRD groups: 42% of the dialysis and 29% of the transplanted patients were taking these drugs.”

“In general, the prevalence of RH was 7.9% for all patients with type 1 diabetes (n = 3,678) and 21.2% for the antihypertensive drug–treated patients (n = 1,370). The proportion was higher in men than in women (10.0 vs. 5.7%, P < 0.0001) […] When the patients were stratified by nephropathy status, the figures changed; in the normoalbuminuria group, the prevalence of RH was 1.2% of all and 8.7% of the drug treated patients. The corresponding numbers were 4.7 and 7.8% for the microalbuminuric patients, 28.1 and 31.2% for the macroalbuminuric patients, 36.6 and 41.3% for the patients on dialysis, and 26.3 and 28.8% for the kidney-transplanted patients, respectively […] The prevalence of RH also increased along with the worsening of renal function. The share was 1.4% for all and 7.4% for drug-treated patients at KDOQI stage 1. The corresponding numbers were 3.8 and 10.0% for the patients at stage 2, 26.6 and 30.0% for the patients at stage 3, 54.8 and 56.0% for the patients at stage 4, and 48.0 and 52.1% for those at stage 5, when kidney transplantation patients were excluded. […] In a multivariate logistic regression analysis, higher age, lower eGFR, higher waist-to-hip ratio, higher triglycerides, as well as microalbuminuria and macroalbuminuria, when normoalbuminuria was the reference category, were independently associated with RH […] A separate analysis also showed that dietary sodium intake, based on urinary sodium excretion rate, was independently associated with RH.”

“The current study shows that the prevalence of RH in patients with type 1 diabetes increases alongside the worsening of diabetic nephropathy. Whereas less than one-tenth of the antihypertensive drug–treated patients with normo- or microalbuminuria met the criteria for RH, the proportions were substantially higher among the patients with overt nephropathy: one-third of the patients with macroalbuminuria or a transplanted kidney and even 40% of the patients on dialysis. […] the prevalence of RH for the drug-treated patients was even higher (56%) in patients at the predialysis stage (eGFR 15–29). The findings are consistent with other studies that have demonstrated that chronic kidney disease is a strong predictor of failure to achieve BP targets despite the use of three or more different types of antihypertensive drugs in the general hypertensive population (26).”

“The prevalence of RH was 21.2% of the patients treated with antihypertensive drugs. Previous studies have indicated a prevalence of RH of 13% among patients being treated for hypertension (1921,27). […] the prevalence [of RH] seems to be […] higher among the drug-treated type 1 diabetic patients. These figures can only partly be explained by the use of a lower treatment target for BP, as recommended for patients with diabetes (6), since even when we used the BP target recommended for hypertensive patients (<140/90 mmHg), our data still showed a higher prevalence of RH (17%).”

“The study also confirmed previous findings that a large number of patients with type 1 diabetes do not achieve the recommended BP targets. Although the prevalence of RH increased with the severity of diabetic nephropathy, our data also suggest that patients with normo- and microalbuminuria might have a suboptimal drug regimen, since the majority of those who had not reached the BP target were taking only one antihypertensive drug. […] There is therefore an urgent need to improve antihypertensive treatment, not only in patients with overt nephropathy but also in those who have elevated BP without complications or early signs of renal disease. Moreover, further emphasis should be placed on the transplanted patients, since it is well known that hypertension affects both graft and patient survival negatively (30).” (my bold)

v. Association of Autoimmunity to Autonomic Nervous Structures With Nerve Function in Patients With Type 1 Diabetes: A 16-Year Prospective Study.

“Neuropathy is a chronic complication that includes a number of distinct syndromes and autonomic dysfunctions and contributes to increase morbidity and mortality in the diabetic population. In particular, cardiovascular autonomic neuropathy (CAN) is an independent risk factor for mortality in type 1 diabetes and is associated with poor prognosis and poor quality of life (13). Cardiovascular (CV) autonomic regulation rests upon a balance between sympathetic and parasympathetic innervation of the heart and blood vessels controlling heart rate and vascular dynamics. CAN encompasses several clinical manifestations, from resting tachycardia to fatal arrhythmia and silent myocardial infarction (4).

The mechanisms responsible for altered neural function in diabetes are not fully understood, and it is assumed that multiple mutually perpetuating pathogenic mechanisms may concur. These include dysmetabolic injury, neurovascular insufficiency, deficiency of neurotrophic growth factors and essential fatty acids, advanced glycosylation products (5,6), and autoimmune damage. Independent cross-sectional and prospective (713) studies identified circulating autoantibodies to autonomic nervous structures and hypothesized that immune determinants may be involved in autonomic nerve damage in type 1 diabetes. […] However, demonstration of a cause–effect relationship between antibodies (Ab) and diabetic autonomic neuropathy awaits confirmation.”

“We report on a 16-year follow-up study specifically designed to prospectively examine a cohort of patients with type 1 diabetes and aimed at assessing whether the presence of circulating Ab to autonomic nervous structures is associated with increased risk and predictive value of developing CAN. This, in turn, would be highly suggestive of the involvement of autoimmune mechanisms in the pathogenesis of this complication.”

“The present prospective study, conducted in young patients without established autonomic neuropathy at recruitment and followed for over 16 years until adulthood, strongly indicates that a cause–effect relationship may exist between auto-Ab to autonomic nervous tissues and development of diabetic autonomic neuropathy. Incipient or established CAN (22) reached a prevalence of 68% among the Ab-positive patients, significantly higher compared with the Ab-negative patients. […] Logistic regression analysis indicates that auto-Ab carry an almost 15-fold increased RR of developing an abnormal DB [deep breathing] test over 16 years and an almost sixfold increase of developing at least one abnormal CV [cardiovascular] test, independent of other variables. […] Circulating Ab to autonomic structures are associated with the development of autonomic dysfunction in young diabetic patients independent of glycemic control. […] autoimmune mechanisms targeting sympathetic and parasympathetic structures may play a primary etiologic role in the development and progression of autonomic dysfunction in type 1 diabetes in the long term. […] positivity for auto-Ab had a high positive predictive value for the later development of autonomic neuropathy.”

“Diabetic autonomic neuropathy, possibly the least recognized and most overlooked of diabetes complications, has increasingly gained attention as an independent predictor of silent myocardial ischemia and mortality, as consistently indicated by several cross-sectional studies (2,3,33). The pooled prevalence rate risk for silent ischemia is estimated at 1.96 by meta-analysis studies (5). In this report, established CAN (22) was detected in nearly 20% of young adult patients with acceptable metabolic control, after over approximately 23 years of diabetes duration, against 12% of patients of the same cohort with subtle asymptomatic autonomic dysfunction (one abnormal CV test) a decade earlier, in line with other studies in type 1 diabetes (2,24). Approximately 30% of the patients developed signs of peripheral somatic neuropathy not associated with autonomic dysfunction. This discrepancy suggests the participation of pathogenic mechanisms different from metabolic control and a distinct clinical course, as indicated by the DCCT study, where hyperglycemia had a less robust relationship with autonomic than somatic neuropathy (6).”

“Furthermore, this study shows that autonomic neuropathy, together with female sex and the occurrence of severe hypoglycemia, is a major determinant for poor quality of life in patients with type 1 diabetes. This is in agreement with previous reports (35) and linked to such invalidating symptoms as orthostatic hypotension and chronic diarrhea. […] In conclusion, the current study provides persuasive evidence for a primary pathogenic role of autoimmunity in the development of autonomic diabetic neuropathy. However, the mechanisms through which auto-Ab impair their target organ function, whether through classical complement action, proapoptotic effects of complement, enhanced antigen presentation, or channelopathy (26,39,40), remain to be elucidated.” (my bold)

vi. Body Composition Is the Main Determinant for the Difference in Type 2 Diabetes Pathophysiology Between Japanese and Caucasians.

“According to current understanding, the pathophysiology of type 2 diabetes is different in Japanese compared with Caucasians in the sense that Japanese are unable to compensate insulin resistance with increased insulin secretion to the same extent as Caucasians. Prediabetes and early stage diabetes in Japanese are characterized by reduced β-cell function combined with lower degree of insulin resistance compared with Caucasians (810). In a prospective, cross-sectional study of individuals with normal glucose tolerance (NGT) and impaired glucose tolerance (IGT), it was demonstrated that Japanese in Japan were more insulin sensitive than Mexican Americans in the U.S. and Arabs in Israel (11). The three populations also differed with regards to β-cell response, whereas the disposition index — a measure of insulin secretion relative to insulin resistance — was similar across ethnicities for NGT and IGT participants. These studies suggest that profound differences in type 2 diabetes pathophysiology exist between different populations. However, few attempts have been made to establish the underlying demographic or lifestyle-related factors such as body composition, physical fitness, and physical activity leading to these differences.”

“The current study aimed at comparing Japanese and Caucasians at various glucose tolerance states, with respect to 1) insulin sensitivity and β-cell response and 2) the role of demographic, genetic, and lifestyle-related factors as underlying predictors for possible ethnic differences in insulin sensitivity and β-cell response. […] In our study, glucose profiles from OGTTs [oral glucose tolerance tests] were similar in Japanese and Caucasians, whereas insulin and C-peptide responses were lower in Japanese participants compared with Caucasians. In line with these observations, measures of β-cell response were generally lower in Japanese, who simultaneously had higher insulin sensitivity. Moreover, β-cell response relative to the degree of insulin resistance as measured by disposition indices was virtually identical in the two populations. […] We […] confirmed the existence of differences in insulin sensitivity and β-cell response between Japanese and Caucasians and showed for the first time that a major part of these differences can be explained by differences in body composition […]. On the basis of these results, we propose a similar pathophysiology of type 2 diabetes in Caucasians and Japanese with respect to insulin sensitivity and β-cell function.”


October 12, 2017 - Posted by | Cardiology, Diabetes, Epidemiology, Health Economics, Medicine, Nephrology, Neurology, Pharmacology, Studies

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