Econstudentlog

Words

Most of the words below are words which I encountered while reading the books 100 cases in emergency medicine and critical care, Frozen Assets, Money in the Bank, Ice in the bedroom, Treason’s Harbour, Earth, Air, Fire and Custard, and May Contain Traces of Magic.

Talus/talar. Mortise. Empyema. Tragus. Otorrhoea. Lordosis. Chemosis. Eversion. Coryza. Atopy. Ectropion. Fly-tipping. Favism. Quillet. Hyperthymesia. Barratry. Simoom. Corium. Inexpugnable. Sly.

Portentous. Distaff. Dipsomaniac. Peart. Nippy. Frenetic. Azeotrope. Tumbril. Ratty. Exordium. Zareba. Bezel. Gregale. Gaberlunzie. Chelengk. Deboshed. Coriaceous. Battel. Rufous. Skink.

Lascar. Milksop. Polenta. Compline. Zither. Stroppy. Calomel. Spangly. Postern. Unregenerate. Vertiginous. Judder. Perspex. Swizzle. Lambently. Sprog. Flollop. Dodgem. Prurient. Gazump.

Cathexis. Scrounge. Quaerens. Tine. Tape measure. Strimmer. Bardiche. Martel. Demiurge. Copra. Grubby. Stonking. Campanology. Taramasalata. Muliebrity. Slumgullion. Flocculate. Mollycoddle. Bloviate. Kitsch.

 

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May 20, 2018 Posted by | Books, Language | Leave a comment

Alcohol and Aging

I’m currently reading this book. Below I have added some observations from the first five chapters. The book has 17 chapters in total, covering a wide variety of topics. I like the coverage so far. All the highlighted observations below were highlighted by me; they were not written in bold in the book.

“Alcohol consumption and alcohol-related deaths or problems have recently increased among older age groups in many developed countries […]. This increase in consumption, in combination with the ageing of populations worldwide, means that the absolute number of older people with alcohol problems is on the increase and a real danger exists that a “silent epidemic” may be evolving [2]. Although there is growing recognition of this public health problem, clinicians consistently under-detect alcohol problems and under-deliver behaviour change interventions to older people [8, 9] […] While older adults historically demonstrate much lower rates of alcohol use compared with younger adults [4, 5] and present to substance abuse treatment programs less frequently than their younger counterparts [6], substantial evidence suggests that at-risk alcohol use and alcohol use disorder (AUD) among older adults has been under-identified for decades [7, 8]. […] Individuals who have had alcohol-related problems over several decades and have survived into old age tend to be referred to as early onset drinkers. It is estimated that two-thirds of older drinkers fall into this category [2]. […] Late-onset drinking accounts for the remaining one-third of older people who use alcohol excessively [2]. Late-onset drinkers usually begin drinking in their 50s or 60s and tend to be of a higher socio-economic status than early onset drinkers with higher levels of education and income [2]. Stressful life events, such as bereavement or retirement, may trigger late-onset drinking […]. One study demonstrated that 70 % of late-onset drinkers had experienced stressful life events, compared with 25 % of early onset drinkers [17]. Those whose alcohol problems are of late onset tend to have fewer health problems and are more receptive to treatment than those with early onset problems […] Our data highlighted that losing a parent or partner was often pinpointed as an event that had prompted an escalation in alcohol use […] A recent systematic review which examined the relationship between late-life spousal bereavement and changes in routine health behaviour over 32 different studies [however] found only moderate evidence for increased alcohol consumption [41].”

“Understanding alcohol use among older adults requires a life course perspective [2] […]. Broadly speaking, to understand alcohol consumption patterns and associated risks among older adults, one must consider both biopsychosocial processes that emerge earlier in life and aging-specific processes, such as multimorbidity and retirement. […] In the population overall, older adulthood is a life stage in which overall alcohol consumption decreases, binge drinking becomes less common, and individuals give up drinking. […] data collected internationally supports the assertion that older adulthood is a period of declining drinking. […] Two forces specific to later life may be at work in decreasing levels of alcohol consumption in late life. First, the “sick-quitter” hypothesis [12, 13] suggests that changes in health during the aging process limit alcohol consumption. With declines in health, older adults decrease the quantity and frequency of their drinking leading to lower average consumption in the overall older adult population [11, 14]. Similarly, differential mortality of heavy drinkers may lead to decreases in alcohol use among cohorts of older adults; these changes in average drinking may be a function of early mortality of heavy drinkers [15]. Although alcohol use generally declines throughout the course of older adulthood, the population of older adults exhibits a great deal of variability in drinking patterns. […] longitudinal research studies have found that older men tend to consume alcohol at higher levels than women, and their consumption levels decline more slowly than women’s [6]. […] National survey data [from the UK] estimate that approximately 40–45% of older adults (65+) drank alcohol in the past year […] Numerous studies suggest that lifetime nondrinkers are more likely to be female, display greater religiosity (e.g., attend religious services), and have lower levels of education than their moderate drinking peers [20, 21]. […] Older adult nondrinkers are a heterogeneous population, and as such, lifetime nondrinkers and former drinkers should be studied separately. This is especially important when considering the issue of health and drinking because the context for abstinence may be different in these two groups [23, 24].”

“[V]ersion 5 of the DSM manual abandoned separate alcohol abuse and alcohol dependence diagnoses, and combined them into a single diagnosis: alcohol use disorder (AUD). […] The NSDUH survey estimated a past-year prevalence rate of alcohol abuse or dependence of 6.1 % among those aged 50–54 and 2.2 % among those ages 65 and older. […] AUD is the most severe manifestation of alcohol-related pathology among older adults, but most alcohol-related harm is not a function of disordered drinking [55]. […] older adults commonly take medications that interact with alcohol. A recent study of community-dwelling older adults (aged 57+) found that 41% consumed alcohol regularly and among regular alcohol consumers, 51 % used at least one alcohol interacting medication [57]. An analysis of the Irish Longitudinal Study on Ageing identified a high prevalence of alcohol use (60 %) among individuals taking alcohol interacting medications [58]. Falls are also a common health concern for older adults, and there is evidence of increased risk of falls among older adults who drink more than 14 drinks per week [59] […] a study by Holahan and colleagues [44] explored longitudinal outcomes for individuals who were moderate drinkers (below the weekly at-risk threshold) but who engaged in heavy episodic drinking (exceeded day threshold). Individuals were first surveyed between the ages of 55 and 65 and followed for 20 years. Episodic heavy drinkers were twice as likely to have died in the 20-year follow-up period compared with those who were not episodic heavy drinkers […to clarify, none of the episodic heavy drinkers in that study would qualify for a diagnosis of AUD, US] […] Alcohol use in the aging population has been defined through various thresholds of risk. Each approach brings certain advantages and problems. Using alcohol related disorders as a benchmark misses many older adults who may experience alcohol-related consequences to their health and well-being even though they do not meet criteria for disordered drinking. More conservative measures of alcohol risk may identify at-risk drinking in those for whom alcohol use may never compromise their health. […] among light to moderate drinkers, the level of risk is uncertain.

Among adults 65 years old and older in 2000–2001, just under 49.6% reported lifetime use [of tobacco] and 14% reported use in the last 12 months [30]. […] Data collected by the Centers for Disease Control in 2008 revealed that only 9% of individuals aged 65 and older reported being current smokers [42]. […] data from the 2001–2002 NESARC reveal a strong relationship between AUDs and tobacco use […] in 2012, 19.3% of adults 65 and older reported having ever used illicit drugs in their lifetime, whereas 47.6% of adults between the ages 60 and 64 reported lifetime drug use. […] In the 2005–2006 NSDUH […] 3.9% of adults aged 50–64, the bulk of the Baby Boomers at that time, reported past year marijuana use, compared to only 0.7% of those 65 years old and older [53]. Among those aged 50 and older reporting marijuana use, 49% reported using marijuana more than 30 days in the past year, with a mean of 81 days. […] The increasingly widespread, legal availability and acceptance of cannabis, for both medicinal and recreational use, may pose unique risks in an aging population. Across age groups, cannabis is known to impair short-term memory, increase one’s heart and respiratory rate, and elevate blood pressure [56]. […] For older adults, these risks may be particularly pronounced, especially for those whose cognitive or cardiovascular systems may already be compromised. […] Most researchers generally consider existing estimations of mental health and substance use disorders to be underestimations among older adults. […] Assumptions that older adults do not drink or use illicit substances should not be made.

“Although several studies in the United States and elsewhere have shown that moderate alcohol consumption is associated with reduced risk for heart disease [16–20] and that heavy intake is associated with increased risk of CVD incidence [6, 21] and all-cause mortality in various populations […], data specific to effects of alcohol in elderly populations remain scant. The few studies available, e.g., the Cardiovascular Health Study, suggest that moderate alcohol use is beneficial and may be associated with reduced Medicare costs among individuals with CVD [25]. The benefits and risks of alcohol consumption are dose dependent with a consistent cut-point for cardiovascular benefits being 1 drink per day for women and about 2 drinks per day for men [21]. These cut-points have also been observed for associations between alcohol consumption and all-cause mortality [21, 26]. Although there are many similarities in the effects of alcohol on CVD across many populations, the magnitude and significance of the association between amount of alcohol consumed and CVD risk remain inconsistent, especially within countries, regions, age, sex, race, and other population strata […] As shown in a recent review [33], a drinking pattern characterized by moderate drinking without episodes of heavy drinking may be more beneficial for CVD protection when compared to patterns that include heavy drinking episodes. […] In additional to amount of alcohol consumed per se, the pattern of alcohol consumption, commonly defined as the number of drinking days per week is also associated with CVD outcomes independent of the amount of alcohol consumed [18, 24, 34–37]. In general, a drinking pattern characterized by alcohol consumption on 4 or more days of the week is inversely associated with MI, stroke, and CVD risk factors“.

“The relation between moderate alcohol consumption and intermediate CVD markers was summarized in two recent reviews [6, 42]. Overall, moderate alcohol consumption is associated with improved concentrations of CVD risk markers, particularly HDL-C concentrations [18, 31, 43, 44]. Whether HDL-C resulting from moderate alcohol intake is functional and beneficial for cardioprotection remains unknown […] While moderate alcohol consumption shows no appreciable benefit on LDL-C, it is associated with significant improvement in insulin sensitivity […] Alcohol intake may also influence CVD markers through its effects on absorption and metabolism of nutrients in the body. This is critical especially in the elderly who may have deficiencies or insufficiencies of nutrients such as folate, vitamin B12, vitamin D, magnesium, and iron. Indeed, moderate alcohol consumption has been shown to improve status of nutrients associated with cardiovascular effects. For example, it improves iron absorption in humans [52, 53] and is associated with higher vitamin D levels in men [54]. […] heavy alcohol consumption [on the other hand] leads to deficiencies of magnesium [55], zinc, folate [56], and other nutrients and damages the intestinal lining and the liver impairing nutrient absorption and metabolism [57]. These effects of alcohol are likely to be worse in the elderly. […] chronic heavy drinking lowers magnesium [55], a nutrient needed for proper metabolism of vitamin D [58], implying that supplementation with vitamin D in heavy drinkers may not be as effective as intended. These effects of alcohol could also extend to prescription medications that are in common use among the elderly. […] Taken together, moderate alcohol seems to protect against cardiovascular disease across the whole life span but the data on older age groups are scanty. Theoretical considerations as well as emerging data on intermediate outcomes such as lipids, suggest that moderate alcohol could beneficially interact with medications such as statins to improve cardiovascular health but heavy alcohol could worsen CVD risk, especially in the elderly.”

Alcohol is one of the main risk factors for cancer, with alcohol use attributed to up to 44% of some cancers [2, 3] and between 3.2 and 3.7 % of all cancer deaths [4, 5]. Since 1988, alcohol has been classified as a carcinogen [6]. Types of cancers linked to alcohol use include cancers of the liver, pancreas, esophagus, breast, pharynx, and larynx with most convincing evidence for alcohol-related cancers of the upper aerodigestive tract, stomach, colorectum, liver, and the lungs [2, 7]. All of these cancers have a much higher incidence and mortality rate in older adults […] For alcohol-associated cancers, 66–95% of new cases appear in those 55 years of age or older [8, 9]. For alcohol-associated cancers, other than breast cancer, 75–95 % of new cases occur in those 55 years of age or older [8, 10, 11]. […] Four countries with a decline in alcohol use (France, the UK, Sweden, and US) have […] demonstrated a stabilization or decline in the incidence and mortality rates for types of cancers closely associated with alcohol use [12]. […] The increased risk for cancer related to alcohol use is based on a combination of both quantity/frequency and duration of use, with those consuming alcohol for 20 or more years at increased risk [14]. […] consumption of alcohol at lower levels may also increase the risk for alcohol-related cancers. Nelson et al. reported that daily consumption of 1.5 drinks or greater accounted for 26–35% of alcohol-attributable deaths [5]. Thus, the evidence is growing that daily drinking, even at lower levels, increases the risk for developing cancer in later life with the conclusion that there may be no safe threshold level for alcohol consumption below which there is no risk for cancer [6, 16, 17].”

The risk for developing alcohol-related cancer is increased among those who have a history of concurrent tobacco use and at-risk alcohol use […] Among individuals who have a history of smoking two or more packs of cigarettes and consuming more than four alcoholic drinks per day, the risk of head and neck cancer is increased greater than 35-fold [22]. […] At least 75 % of head and neck cancer is associated with alcohol and tobacco use[9]. […] There are gender differences in alcohol attributable cancer deaths with over half (56–66 %) of all alcohol-attributable cancer deaths in females resulting from breast cancer [5]. […] For women, even low-risk alcohol use (5–14.9 g/day or one standard drink of alcohol or less) increases the risk of cancer, mainly breast cancer [18]. […] Alcohol use during cancer treatment can complicate the treatment regimen and lead to poor long-term outcomes. […] Alcohol use is correlated with poor survival outcomes in oncology patients. […] Another issue for patients during cancer treatment is quality of life. Alcohol consumption at higher levels […] or patients who screened positive for a possible AUD during cancer treatment experienced worse quality of life outcomes, including problems with pain, sleep, dyspnea, total distress, anxiety, coping, shortness of breath, diarrhea, poor emotional functioning, fatigue, and poor appetite [58, 59]. Current alcohol use has also been associated with higher pain scores and long-term use of opioids [48, 49].”

May 14, 2018 Posted by | Books, Cancer/oncology, Cardiology, Epidemiology, Medicine | Leave a comment

Quotes

i. “Never esteem anything as of advantage to you that will make you break your word or lose your self-respect.” (Marcus Aurelius)

ii. “Waste no more time arguing what a good man should be. Be one.” (-ll-)

iii. “If it is not right, do not do it, if it is not true, do not say it.” (-ll-)

iv. “Nothing has such power to broaden the mind as the ability to investigate systematically and truly all that comes under thy observation in life.” (-ll-)

v. “The best revenge is not to be like your enemy.” (-ll-)

vi. “Memories are like flagstones, time and distance work upon them like drops of acid.” (Ugo Betti)

vii. “We have all forgot more than we remember.” (Thomas Fuller)

viii. “The free market in ideas has never been free, but always a market.” (Russell Jacoby)

ix. “Practical politics consists in ignoring facts.” (Henry Adams)

x. “Nowhere do men remain loyal for long when Fortune proves unstable.” (Silius Italicus)

xi. “The sin of thousands always goes unpunished.” (Lucan)

xii. “Software engineering is the part of computer science which is too difficult for the computer scientist.” (Friedrich Bauer)

xiii. “What we call human reason, is not the effort or ability of one, so much as it is the result of the reason of many, arising from lights mutually communicated, in consequence of discourse and writing.” (Hugh Blair)

xiv. “Universities should be safe havens where ruthless examination of realities will not be distorted by the aim to please or inhibited by the risk of displeasure.” (Kingman Brewster, Jr.)

xv. “To be left alone is the most precious thing one can ask of the modern world.” (Anthony Burgess)

xvi. “It is no great accomplishment to take people as they are, and we must always do so eventually, but to wish them to be as they are, that is a genuine love.” (Émile Chartier)

xvii. “In religion, faith is a virtue. In science, faith is a vice.” (Jerry Coyne)

xviii. “No one will ever follow you down the street if you’re carrying a banner that says, “Onward toward mediocrity.”” (Martin de Maat)

xix. “Blame the process, not the people.” (W. Edwards Deming)

xx. “One of life’s best coping mechanisms is to know the difference between an inconvenience and a problem. If you break your neck, if you have nothing to eat, if your house is on fire, then you’ve got a problem. Everything else is an inconvenience. Life is inconvenient. Life is lumpy. A lump in the oatmeal, a lump in the throat and a lump in the breast are not the same kind of lump. One needs to learn the difference.” (Robert Fulghum)

May 10, 2018 Posted by | Quotes/aphorisms | 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

Molecular biology (I?)

“For a brief while I was considering giving this book five stars, but it didn’t quite get there. However this is a great publication, considering the format. These authors in my opinion managed to get quite close to what I’d consider to be ‘the ideal level of coverage’ for books of this nature.”

The above was what I wrote in my short goodreads review of the book. In this post I’ve added some quotes from the first chapters of the book and some links to topics covered.

Quotes:

“Once the base-pairing double helical structure of DNA was understood it became apparent that by holding and preserving the genetic code DNA is the source of heredity. The heritable material must also be capable of faithful duplication every time a cell divides. The DNA molecule is ideal for this. […] The effort then concentrated on how the instructions held by the DNA were translated into the choice of the twenty different amino acids that make up proteins. […] George Gamov [yes, that George Gamov! – US] made the suggestion that information held in the four bases of DNA (A, T, C, G) must be read as triplets, called codons. Each codon, made up of three nucleotides, codes for one amino acid or a ‘start’ or ‘stop’ signal. This information, which determines an organism’s biochemical makeup, is known as the genetic code. An encryption based on three nucleotides means that there are sixty-four possible three-letter combinations. But there are only twenty amino acids that are universal. […] some amino acids can be coded for by more than one codon.”

“The mechanism of gene expression whereby DNA transfers its information into proteins was determined in the early 1960s by Sydney Brenner, Francois Jacob, and Matthew Meselson. […] Francis Crick proposed in 1958 that information flowed in one direction only: from DNA to RNA to protein. This was called the ‘Central Dogma‘ and describes how DNA is transcribed into RNA, which then acts as a messenger carrying the information to be translated into proteins. Thus the flow of information goes from DNA to RNA to proteins and information can never be transferred back from protein to nucleic acid. DNA can be copied into more DNA (replication) or into RNA (transcription) but only the information in mRNA [messenger RNA] can be translated into protein”.

“The genome is the entire DNA contained within the forty-six chromosomes located in the nucleus of each human somatic (body) cell. […] The complete human genome is composed of over 3 billion bases and contain approximately 20,000 genes that code for proteins. This is much lower than earlier estimates of 80,000 to 140,000 and astonished the scientific community when revealed through human genome sequencing. Equally surprising was the finding that genomes of much simpler organisms sequenced at the same time contained a higher number of protein-coding genes than humans. […] It is now clear that the size of the genome does not correspond with the number of protein-coding genes, and these do not determine the complexity of an organism. Protein-coding genes can be viewed as ‘transcription units’. These are made up of sequences called exons that code for amino acids, and separated by by non-coding sequences called introns. Associated with these are additional sequences termed promoters and enhancers that control the expression of that gene.”

“Some sections of the human genome code for RNA molecules that do not have the capacity to produce proteins. […] it is now becoming apparent that many play a role in controlling gene expression. Despite the importance of proteins, less than 1.5 per cent of the genome is made up of exon sequences. A recent estimate is that about 80 per cent of the genome is transcribed or involved in regulatory functions with the rest mainly composed of repetitive sequences. […] Satellite DNA […] is a short sequence repeated many thousands of times in tandem […] A second type of repetitive DNA is the telomere sequence. […] Their role is to prevent chromosomes from shortening during DNA replication […] Repetitive sequences can also be found distributed or interspersed throughout the genome. These repeats have the ability to move around the genome and are referred to as mobile or transposable DNA. […] Such movements can be harmful sometimes as gene sequences can be disrupted causing disease. […] The vast majority of transposable sequences are no longer able to move around and are considered to be ‘silent’. However, these movements have contributed, over evolutionary time, to the organization and evolution of the genome, by creating new or modified genes leading to the production of proteins with novel functions.”

“A very important property of DNA is that it can make an accurate copy of itself. This is necessary since cells die during the normal wear and tear of tissues and need to be replenished. […] DNA replication is a highly accurate process with an error occurring every 10,000 to 1 million bases in human DNA. This low frequency is because the DNA polymerases carry a proofreading function. If an incorrect nucleotide is incorporated during DNA synthesis, the polymerase detects the error and excises the incorrect base. Following excision, the polymerase reinserts the correct base and replication continues. Any errors that are not corrected through proofreading are repaired by an alternative mismatch repair mechanism. In some instances, proofreading and repair mechanisms fail to correct errors. These become permanent mutations after the next cell division cycle as they are no longer recognized as errors and are therefore propagated each time the DNA replicates.”

DNA sequencing identifies the precise linear order of the nucleotide bases A, C, G, T, in a DNA fragment. It is possible to sequence individual genes, segments of a genome, or whole genomes. Sequencing information is fundamental in helping us understand how our genome is structured and how it functions. […] The Human Genome Project, which used Sanger sequencing, took ten years to sequence and cost 3 billion US dollars. Using high-throughput sequencing, the entire human genome can now be sequenced in a few days at a cost of 3,000 US dollars. These costs are continuing to fall, making it more feasible to sequence whole genomes. The human genome sequence published in 2003 was built from DNA pooled from a number of donors to generate a ‘reference’ or composite genome. However, the genome of each individual is unique and so in 2005 the Personal Genome Project was launched in the USA aiming to sequence and analyse the genomes of 100,000 volunteers across the world. Soon after, similar projects followed in Canada and Korea and, in 2013, in the UK. […] To store and analyze the huge amounts of data, computational systems have developed in parallel. This branch of biology, called bioinformatics, has become an extremely important collaborative research area for molecular biologists drawing on the expertise of computer scientists, mathematicians, and statisticians.”

“[T]he structure of RNA differs from DNA in three fundamental ways. First, the sugar is a ribose, whereas in DNA it is a deoxyribose. Secondly, in RNA the nucleotide bases are A, G, C, and U (uracil) instead of A, G, C, and T. […] Thirdly, RNA is a single-stranded molecule unlike double-stranded DNA. It is not helical in shape but can fold to form a hairpin or stem-loop structure by base-pairing between complementary regions within the same RNA molecule. These two-dimensional secondary structures can further fold to form complex three-dimensional, tertiary structures. An RNA molecule is able to interact not only with itself, but also with other RNAs, with DNA, and with proteins. These interactions, and the variety of conformations that RNAs can adopt, enables them to carry out a wide range of functions. […] RNAs can influence many normal cellular and disease processes by regulating gene expression. RNA interference […] is one of the main ways in which gene expression is regulated.”

“Translation of the mRNA to a protein takes place in the cell cytoplasm on ribosomes. Ribosomes are cellular structures made up primarily of rRNA and proteins. At the ribosomes, the mRNA is decoded to produce a specific protein according to the rules defined by the genetic code. The correct amino acids are brought to the mRNA at the ribosomes by molecules called transfer RNAs (tRNAs). […] At the start of translation, a tRNA binds to the mRNA at the start codon AUG. This is followed by the binding of a second tRNA matching the adjacent mRNA codon. The two neighbouring amino acids linked to the tRNAs are joined together by a chemical bond called the peptide bond. Once the peptide bond forms, the first tRNA detaches leaving its amino acid behind. The ribosome then moves one codon along the mRNA and a third tRNA binds. In this way, tRNAs sequentially bind to the mRNA as the ribosome moves from codon to codon. Each time a tRNA molecule binds, the linked amino acid is transferred to the growing amino acid chain. Thus the mRNA sequence is translated into a chain of amino acids connected by peptide bonds to produce a polypeptide chain. Translation is terminated when the ribosome encounters a stop codon […]. After translation, the chain is folded and very often modified by the addition of sugar or other molecules to produce fully functional proteins.”

“The naturally occurring RNAi pathway is now extensively exploited in the laboratory to study the function of genes. It is possible to design synthetic siRNA molecules with a sequence complementary to the gene under study. These double-stranded RNA molecules are then introduced into the cell by special techniques to temporarily knock down the expression of that gene. By studying the phenotypic effects of this severe reduction of gene expression, the function of that gene can be identified. Synthetic siRNA molecules also have the potential to be used to treat diseases. If a disease is caused or enhanced by a particular gene product, then siRNAs can be designed against that gene to silence its expression. This prevents the protein which drives the disease from being produced. […] One of the major challenges to the use of RNAi as therapy is directing siRNA to the specific cells in which gene silencing is required. If released directly into the bloodstream, enzymes in the bloodstream degrade siRNAs. […] Other problems are that siRNAs can stimulate the body’s immune response and can produce off-target effects by silencing RNA molecules other than those against which they were specifically designed. […] considerable attention is currently focused on designing carrier molecules that can transport siRNA through the bloodstream to the diseased cell.”

“Both Northern blotting and RT-PCR enable the expression of one or a few genes to be measured simultaneously. In contrast, the technique of microarrays allows gene expression to be measured across the full genome of an organism in a single step. This massive scale genome analysis technique is very useful when comparing gene expression profiles between two samples. […] This can identify gene subsets that are under- or over-expressed in one sample relative to the second sample to which it is compared.”

Links:

Molecular biology.
Charles Darwin. Alfred Wallace. Gregor Mendel. Wilhelm Johannsen. Heinrich Waldeyer. Theodor Boveri. Walter Sutton. Friedrich Miescher. Phoebus Levene. Oswald Avery. Colin MacLeod. Maclyn McCarty. James Watson. Francis Crick. Rosalind Franklin. Andrew Fire. Craig Mello.
Gene. Genotype. Phenotype. Chromosome. Nucleotide. DNA. RNA. Protein.
Chargaff’s rules.
Photo 51.
Human Genome Project.
Long interspersed nuclear elements (LINEs). Short interspersed nuclear elements (SINEs).
Histone. Nucleosome.
Chromatin. Euchromatin. Heterochromatin.
Mitochondrial DNA.
DNA replication. Helicase. Origin of replication. DNA polymeraseOkazaki fragments. Leading strand and lagging strand. DNA ligase. Semiconservative replication.
Mutation. Point mutation. Indel. Frameshift mutation.
Genetic polymorphism. Single-nucleotide polymorphism (SNP).
Genome-wide association study (GWAS).
Molecular cloning. Restriction endonuclease. Multiple cloning site (MCS). Bacterial artificial chromosome.
Gel electrophoresis. Southern blot. Polymerase chain reaction (PCR). Reverse transcriptase PCR (RT-PCR). Quantitative PCR (qPCR).
GenBank. European Molecular Biology Laboratory (EMBL). Encyclopedia of DNA Elements (ENCODE).
RNA polymerase II. TATA box. Transcription factor IID. Stop codon.
Protein biosynthesis.
SmRNA (small nuclear RNA).
Untranslated region (/UTR sequences).
Transfer RNA.
Micro RNA (miRNA).
Dicer (enzyme).
RISC (RNA-induced silencing complex).
Argonaute.
Lipid-Based Nanoparticles for siRNA Delivery in Cancer Therapy.
Long non-coding RNA.
Ribozyme/catalytic RNA.
RNA-sequencing (RNA-seq).

May 5, 2018 Posted by | Biology, Books, Chemistry, Genetics, Medicine | Leave a comment

Trade-offs when doing medical testing

I was considering whether or not to blog the molecular biology text I recently read today, but I decided against it. However as I did feel like blogging today, I decided instead to add here a few comments I left on SCC. I rarely leave comments on other blogs, but it does happen, and the question I was ‘answering’ (partially – other guys had already added some pretty good comments by the time I joined the debate) is probably a question that I imagine a lot of e.g. undergrads are asking themselves, namely: “What’s the standard procedure, when designing a medical test, to determine the right tradeoff between sensitivity and specificity (where I’m picturing a tradeoff involved in choosing the threshold for a positive test or something similar)?

The ‘short version’, if you want an answer to this question, is probably to read Newman and Kohn’s wonderful book on these- and related- topics (which I blogged here), but that’s not actually a ‘short answer’ in terms of how people usually think about these things. I’ll just reproduce my own comment here, and mention that other guys had already covered some key topics by the time I joined ‘the fray’:

“Some good comments already. I don’t know to which extent the following points have been included in the links provided, but I decided to add them here anyway.

One point worth emphasizing is that you’ll always want a mixture of sensitivity and specificity (or, more broadly, test properties) that’ll mean that your test has clinical relevance. This relates both to the type of test you consider and when/whether to test at all (rather than treat/not treat without testing first). If you’re worried someone has disease X and there’s a high risk of said individual having disease X due to the clinical presentation, some tests will for example be inappropriate even if they are very good at making the distinction between individuals requiring treatment X and individuals not requiring treatment X, for example because they take time to perform that the patient might not have – not an uncommon situation in emergency medicine. If you’re so worried you’d treat him regardless of the test result, you shouldn’t test. And the same goes for e.g. low-sensitivity screens; if a positive test result of a screen does not imply that you’ll actually act on the result of the screen, you shouldn’t perform it (in screening contexts cost effectiveness is usually critically dependent on how you follow up on the test result, and in many contexts inadequate follow-up means that the value of the test goes down a lot […on a related note I have been thinking that I was perhaps not as kind as I could have been when I reviewed Juth & Munthe’s book and I have actually considered whether or not to change my rating of the book; it does give a decent introduction to some key trade-offs with which you’re confronted when you’re dealing with topics related to screening].

Cost effectiveness is another variable that would/should probably (in an ideal world?) enter the analysis when you’re judging what is or is not a good mixture of sensitivity and specificity – you should be willing to pay more for more precise tests, but only to the extent that those more precise tests lead to better outcomes (you’re usually optimizing over patient outcomes, not test accuracy).

Skef also mentions this, but the relative values of specificity and sensitivity may well vary during the diagnostic process; i.e. the (ideal) trade-off will depend on what you plan to use the test for. Is the idea behind testing this guy to make (reasonably?) sure he doesn’t have colon cancer, or to figure out if he needs a more accurate, but also more expensive, test? Screening setups will usually involve a multi-level testing structure, and tests at different levels will not treat these trade-offs the same way, nor should they. This also means that the properties of individual tests can not really be viewed in isolation, which makes the problem of finding ‘the ideal mix’ of test properties (whatever these might be) even harder; if you have three potential tests for example, it’s not enough to compare the tests individually against each other, you’d ideally also want to implicitly take into account that different combinations of tests have different properties, and that the timing of the test may also be an important parameter in the decision problem.”

On a related note I think that in general the idea of looking for some kind of ‘approved method’ that you can use to save yourself from thinking is a very dangerous approach when you’re doing applied statistics. If you’re not thinking about relevant trade-offs and how to deal with them, odds are you’re missing a big part of the picture. If somebody claims to have somehow discovered some simple approach to dealing with all of the relevant trade-offs, well, you should be very skeptical. Statistics usually don’t work like that.

May 4, 2018 Posted by | Medicine, Statistics | 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

Endocrinology (part 6 – neuroendocrine disorders and Paget’s disease)

I’m always uncertain as to how much content to cover when covering books like this one, and I usually cover handbooks in less detail (relatively) than I cover other books because of the amount of work it takes to cover all topics of interest – however I didn’t feel after writing my last post in the series that I had really finished with this book, in terms of blogging it; in fact I remember distinctly feeling a bit annoyed towards the end of writing my fifth post by the fact that I didn’t find that I could justify covering the detailed account of Paget’s disease included in the last part of the chapter, even though all of that stuff was new knowledge to me, and quite interesting – but these posts take some effort, and sometimes I cut them short just to at least blog something, rather than just have an unpublished draft lying around.

In this post I’ll first include some belated coverage of Paget’s disease, which is from the book’s chapter 6, and then I’ll cover some of the stuff included in chapter 8 of the book, about neuroendocrine disorders. Chapter 8 deals exclusively with various types of (usually quite rare) tumours. I decided to not cover chapter 7, which is devoted to paediatric endocrinology.

“Paget’s disease is the result of greatly local bone turnover, which occurs particularly in the elderly […] The 1° abnormality in Paget’s disease is gross overactivity of the osteoclasts, resulting in greatly increased ↑ bone resorption. This secondarily results in ↑ osteoblastic activity. The new bone is laid down in a highly disorganized manner […] Paget’s disease can affect any bone in the skeleton […] In most patients, it affects several sites, but, in about 20% of cases, a single bone is affected (monostotic disease). Typically, the disease will start in one end of a long bone and spread along the bone at a rate of about 1cm per year. […] Paget’s disease alters the mechanical properties of the bone. Thus, pagetic bones are more likely to bend under normal physiological loads and are thus liable to fracture. […] Pagetic bones are also larger than their normal counterparts. This can lead to ↑ arthritis at adjacent joints and to pressure on nerves, leading to neurological compression syndromes and, when it occurs in the skull base, sensorineural deafness.”

“Paget’s disease is present in about 2% of the UK population over the age of 55. It’s prevalence increases with age, and it is more common in ♂ than ♀. Only about 10% of affected patients will have symptomatic disease. […] Most notable feature is pain. […] The diagnosis of Paget’s disease is primarily radiological. […] An isotope bone scan is frequently helpful in assessing the extent of skeletal involvement […] Deafness is present in up to half of cases of skull base Paget’s. • Other neurological complications are rare. […] Osteogenic sarcoma [is a] very rare complication of Paget’s disease. […] Any increase of pain in a patient with Paget’s disease should arouse suspicion of sarcomatous degeneration. A more common cause, however, is resumption of activity of disease. […] Treatment with agents that decrease bone turnover reduces disease activity […] Although such treatment has been shown to help pain, there is little evidence that it benefits other consequences of Paget’s disease. In particular, the deafness of Paget’s disease does not regress after treatment […] Bisphosphonates have become the mainstay of treatment. […] Goals of treatment [are to:] • Minimize symptoms. • Prevent long-term complications. • Normalize bone turnover. • Alkaline phosphatase in normal range. • No actual evidence that treatment achieves this.”

The rest of this post will be devoted to covering topics from chapter 8:

Neuroendocrine cells are found in many sites throughout the body. They are particularly prominent in the GI tract and pancreas and […] have the ability to synthesize, store, and release peptide hormones. […] the majority of neuroendocrine tumours occur within the gastroenteropancreatic axis. […] >50% are traditionally termed carcinoid tumours […] with the remainder largely comprising pancreatic islet cell tumours. • Carcinoid and islet cell tumours are generally slow-growing. […] There is a move towards standardizing the terminology of these tumours […] The term NEN [neuroendocrine neoplasia] included low- and intermediate-grade neoplasia (previously referred to as carcinoid or atypical carcinoid) which are now referred to as neuroendocrine tumours (NETs) and high-grade neoplasia (neuroendocrine carcinoma, NEC). There is a confusing array of classifications of NENs, based on anatomical origin, histology, and secretory activity. • Many of these classifications are well established and widely used.”

“It is important to understand the differences between ‘differentiation’, which is the extent to which the neoplastic cells resemble their non-tumourous counterparts, and ‘grade’, which is the inherent agressiveness of the tumour. […] Neuroendocrine carcinomas are the most aggressive NENs and can be either small or large cell type. […] NENs are diagnosed based on histological features of biopsy specimens. The presenting features of the tumours vary like any other tumour, based on their anatomical location, such as abdominal pain, intestinal obstruction. Many are incidentally discovered during endoscopy or imaging for unrelated conditions. In a database study, 49% of NENs were localized, 24% had regional metastases, and 27% had distant metastases. […] These tumours rarely manifest themselves due to their secretory effect. [This is quite different from some of the other tumours they covered elsewhere in the book – US]  [….] Only a third of patients with neuroendocrine tumours develop symptoms due to hormone secretion.”

“Surgery is the treatment of choice for NENs grades 1 and 2, except in the presence of widespread distant metastases and extensive local invasion. […] Somatostatin analogues (SSA) have relatively minor side effects and provide long-term symptom control. •Octreotide and lanreotide […] reduce the level of biochemical tumour markers in the majority of patients and control symptoms in around 70% of cases. […] A combination of interferon with octreotide has been shown to produce biochemical and symptomatic improvement in patients who have previously had no significant benefit from either drug alone. […] Cytotoxic chemotherapy may be considered in patients with progressive, advanced, or uncontrolled symptomatic disease.”

“Despite the changes in nomenclature of NENs […] the ‘carcinoid crisis’ [apparently also termed ‘malignant carcinoid syndrome‘, US] is still an important descriptive term. It is a potentially life-threatening condition that should be prevented, where possible, and treated as an emergency. • Clinical features include hypotension, tachycardia, arrhythmias, flushing, diarrhoea, broncospasm, and altered sensoriom. […] carcinoid crisis can be triggered by manipulation of the tumours, such as during biopsy, surgery, or palpation. • These result in the release of biologically active compounds from the tumours. […] Carcinoid heart disease […] result in valvular stenosis or regurgitation and eventually heart failure. This condition is seen in 40-50% of patients with carcinoid syndrome and 3-4% of patients with neuroendocrine tumours”.

“An insulinoma is a functioning neuroendocrine tumour of the pancreas that causes hypoglycemia through inappropriate secretion of insulin. • Unlike other neuroendocrine tumours of the pancreas, more than 90% of insulinomas are benign. […] annual incidence of insulinomas is of the order of 1-2 per million population. […] The treatment of choice in all, but poor, surgical candidates is operative removal. […] In experienced surgical hands, the mortality is less than 1%. […] Following the removal of solitary insulinoma [>80% of cases], life expectancy is restored to normal. Malignant insulinomas, with metastases usually to the liver, have a natural history of years, rather than months, and may be controlled with medical therapy or specific antitumour therapy […] • Average 5-year survival estimated to be approximately 35% for malignant insulinomas. […] Gastrinomas are the most common functional malignant pancreatic endocrine tumours. […] The incidence of gastrinomas is 0.5-2/million population/year. […] Gastrin […] is the principal gut hormone stimulating gastric acid secretion. • The Zollinger-Ellison (ZE) syndrome is characterized by gastric acid oversecretion and manifests itself as severe peptic ulcer disease (PUD), gastro-oesophageal reflux, and diarrhoea. […] 10-year survival [in patients with gastrinomas] without liver metastases is 95%. […] Where there are diffuse metastases, […] a 10-year survival of approximately 15% [is observed].”

One of the things I was thinking about before deciding whether or not to blog this chapter was whether the (fortunately!) rare conditions encountered in the chapter really ‘deserved’ to be covered. Unlike what is the case for, say, breast cancer or colon cancer, most people won’t know someone who’ll die from malignant insulinoma. However although these conditions are very rare, I also can’t stop myself from thinking they’re also quite interesting, and I don’t care much about whether I know someone with a disease I’ve read about. And if you think these conditions are rare, well, for glucagonomas “The annual incidence is estimated at 1 per 20 million population”. These very rare conditions really serve as a reminder of how great our bodies are at dealing with all kinds of problems we’ve never even thought about. We don’t think about them precisely because a problem so rarely arises – but just now and then, well…

Let’s talk a little bit more about those glucagonomas:

“Glucagonomas are neuroendocrine tumours that usually arise from the α cells of the pancreas and produce the glucagonoma syndrome through the secretion of glucagon and other peptides derived from the preproglucagon gene. • The large majority of glucagonomas are malignant, but they are also very indolent tumours, and the diagnosis may be overlooked for many years. • Up to 90% of patients will have lymph node or liver metastases at the time of presentation. • They are classically associated with the rash of necrolytic migratory erythema. […] The characteristic rash [….] occurs in >70% of cases […] glucose intolerance is a frequent association (>90%). • Sustained gluconeogenesis also causes amino acid deficiencies and results in protein catabolism which can be associated with unrelenting weight loss in >60% of patients. • Glucagon has a direct suppressive effect on the bone marrow, resulting in a normochromic normocytic anaemia in almost all patients. […] Surgery is the only curative option, but the potential for a complete cure may be as low as 5%.”

“In 1958, Verner and Morrison1 first described a syndrome consisting of refractory watery diarrhoea and hypokalaemia, associated with a neuroendocrine tumour of the pancreas. • The syndrome of watery diarrhea, hypokalaemia and acidosis (WDHA) is due to secretion of vasoactive intestinal polypeptide (VIP). • Tumours that secrete VIP are known as VIPomas. VIPomas account for <10% of islet cell tumours and mainly occur as solitary tumours. >60% are malignant […] The most prominent symptom in most patients is profuse watery diarrhoea […] Surgery to remove the tumour is the treatment of first choice […] and may be curative in around 40% of patients. […] Somatostatin analogues produce effective symptomatic relief from the diarrhoea in most patients. Long-term use does not result in tumour regression. […] Chemotherapy […] has resulted in response rates of >30%.”

So by now we know that somatostatin analogues can provide symptom relief in a variety of contexts when you’re dealing with these conditions. But wait, what happens if you get a functional tumour of the cells that produce somatostatins? Will this mean that you just feel great all the time, or that you at least don’t have any symptoms of disease? Well, not exactly…

Somatostatinomas are very rare neuroendocrine tumours, occurring both in the pancreas and in the duodenum. • >60% are large tumours located in the head or body of the pancreas. • The clinical syndrome may be diagnosed late in the course of disease when metastatic spread to local lymph nodes and the liver has already occurred. […] • Glucose intolerance or frank diabetes mellitus may have been observed for many years prior to the diagnosis and retrospectively often represents the first clinical sign. It is probably due to the inhibitory effect of somatostatin on insulin secretion. • A high incidence of gallstones has been described similar to that seen as a side effect with long-term somatostatin analogue therapy. • Diarrhoea, steatorrhoea, and weight loss appear to be consistent clinical features […this despite the fact that you use the hormone produced by these tumours to manage diarrhea in other endocrine tumours – it’s stuff like this which makes these rare disorders far from boring to read about! US] and may be associated with inhibition of the exocrine pancreas by somatostatin.”

May 1, 2018 Posted by | Books, Cancer/oncology, Cardiology, Diabetes, Epidemiology, Medicine, Neurology, Pharmacology | Leave a comment

Medical Statistics (III)

In this post I’ll include some links and quotes related to topics covered in chapters 4, 6, and 7 of the book. Before diving in, I’ll however draw attention to some of Gerd Gigerenzer’s work as it is quite relevant to in particular the coverage included in chapter 4 (‘Presenting research findings’), even if the authors seem unaware of this. One of Gigerenzer’s key insights, which I consider important and which I have thus tried to keep in mind, unfortunately goes unmentioned in the book; namely the idea that how you communicate risk might be very important in terms of whether or not people actually understand what you are trying to tell them. A related observation is that people have studied these things and they’ve figured out that some types of risk communication are demonstrably better than others at enabling people to understand the issues at hand and the trade-offs involved in a given situation. I covered some of these ideas in a comment on SCC some time ago; if those comments spark your interest you should definitely go read the book).

IMRAD format.
CONSORT Statement (randomized trials).
Equator Network.

“Abstracts may appear easy to write since they are very short […] and often required to be written in a structured format. It is therefore perhaps surprising that they are sometimes poorly written, too bland, contain inaccuracies, and/or are simply misleading.1  The reason for poor quality abstracts are complex; abstracts are often written at the end of a long process of data collection, analysis, and writing up, when time is short and researchers are weary. […] statistical issues […] can lead to an abstract that is not a fair representation of the research conducted. […] it is important that the abstract is consistent with the body of text and that it gives a balanced summary of the work. […] To maximize its usefulness, a summary or abstract should include estimates and confidence intervals for the main findings and not simply present P values.”

“The methods section should describe how the study was conducted. […] it is important to include the following: *The setting or area […] The date(s) […] subjects included […] study design […] measurements used […] source of any non-original data […] sample size, including a justification […] statistical methods, including any computer software used […] The discussion section is where the findings of the study are discussed and interpreted […] this section tends to include less statistics than the results section […] Some medical journals have a specific structure for the discussion for researchers to follow, and so it is important to check the journal’s guidelines before submitting. […] [When] reporting statistical analyses from statistical programs: *Don’t put unedited computer output into a research document. *Extract the relevant data only and reformat as needed […] Beware of presenting percentages for very small samples as they may be misleading. Simply give the numbers alone. […] In general the following is recommended for P values: *Give the actual P value whenever possible. *Rounding: Two significant figures are usually enough […] [Confidence intervals] should be given whenever possible to indicate the precision of estimates. […] Avoid graphs with missing zeros or stretched scales […] a table or graph should stand alone so that a reader does not need to read the […] article to be able to understand it.”

Statistical data type.
Level of measurement.
Descriptive statistics.
Summary statistics.
Geometric mean.
Harmonic mean.
Mode.
Interquartile range.
Histogram.
Stem and leaf plot.
Box and whisker plot.
Dot plot.

“Quantitative data are data that can be measured numerically and may be continuous or discrete. *Continuous data lie on a continuum and so can take any value between two limits. […] *Discrete data do not lie on a continuum and can only take certain values, usually counts (integers) […] On an interval scale, differences between values at different points of the scale have the same meaning […] Data can be regarded as on a ratio scale if the ratio of the two measurements has a meaning. For example we can say that twice as many people in one group had a particular characteristic compared with another group and this has a sensible meaning. […] Quantitative data are always ordinal – the data values can be arranged in a numerical order from the smallest to the largest. […] *Interval scale data are always ordinal. Ratio scale data are always interval scale data and therefore must also be ordinal. *In practice, continuous data may look discrete because of the way they are measured and/or reported. […] All continuous measurements are limited by the accuracy of the instrument used to measure them, and many quantities such as age and height are reported in whole numbers for convenience”.

“Categorical data are data where individuals fall into a number of separate categories or classes. […] Different categories of categorical data may be assigned a number for coding purposes […] and if there are several categories, there may be an implied ordering, such as with stage of cancer where stage I is the least advanced and stage IV is the most advanced. This means that such data are ordinal but not interval because the ‘distance’ between adjacent categories has no real measurement attached to it. The ‘gap’ between stages I and II disease is not necessarily the same as the ‘gap’ between stages III and IV. […] Where categorical data are coded with numerical codes, it might appear that there is an ordering but this may not necessarily be so. It is important to distinguish between ordered and non-ordered data because it affects the analysis.”

“It is usually useful to present more than one summary measure for a set of data […] If the data are going to be analyzed using methods based on means then it makes sense to present means rather than medians. If the data are skewed they may need to be transformed before analysis and so it is best to present summaries based on the transformed data, such as geometric means. […] For very skewed data rather than reporting the median, it may be helpful to present a different percentile (i.e. not the 50th), which better reflects the shape of the distribution. […] Some researchers are reluctant to present the standard deviation when the data are skewed and so present the median and range and/or quartiles. If analyses are planned which are based on means then it makes sense to be consistent and give standard deviations. Further, the useful relationship that approximately 95% of the data lie between mean +/- 2 standard deviations, holds even for skewed data […] If data are transformed, the standard deviation cannot be back-transformed correctly and so for transformed data a standard deviation cannot be given. In this case the untransformed standard deviation can be given or another measure of spread. […] For discrete data with a narrow range, such as stage of cancer, it may be better to present the actual frequency distribution to give a fair summary of the data, rather than calculate a mean or dichotomize it. […] It is often useful to tabulate one categorical variable against another to show the proportions or percentages of the categories of one variable by the other”.

Random variable.
Independence (probability theory).
Probability.
Probability distribution.
Binomial distribution.
Poisson distribution.
Continuous probability distribution.
Normal distribution.
Uniform distribution.

“The central limit theorem is a very important mathematical theorem that links the Normal distribution with other distributions in a unique and surprising way and is therefore very useful in statistics. *The sum of a large number of independent random variables will follow an approximately Normal distribution irrespective of their underlying distributions. *This means that any random variable which can be regarded as a the sum of a large number of small, independent contributions is likely to follow the Normal distribution. [I didn’t really like this description as it’s insufficiently detailed for my taste (and this was pretty much all they wrote about the CLT in that chapter); and one problem with the CLT is that people often think it applies when it might not actually do so, because the data restrictions implied by the theorem(s) are not really fully appreciated. On a related note people often seem to misunderstand what these theorems actually say and where they apply – see e.g. paragraph 10 in this post. See also the wiki link above for a more comprehensive treatment of these topicsUS] *The Normal distribution can be used as an approximation to the Binomial distribution when n is large […] The Normal distribution can be used as an approximation to the Poisson distribution as the mean of the Poisson distribution increases […] The main advantage in using the Normal rather than the Binomial or the Poisson distribution is that it makes it easier to calculate probabilities and confidence intervals”

“The t distribution plays an important role in statistics as the sampling distribution of the sample mean divided by its standard error and is used in significance testing […] The shape is symmetrical about the mean value, and is similar to the Normal distribution but with a higher peak and longer tails to take account of the reduced precision in smaller samples. The exact shape is determined by the mean and variance plus the degrees of freedom. As the degrees of freedom increase, the shape comes closer to the Normal distribution […] The chi-squared distribution also plays an important role in statistics. If we take several variables, say n, which each follow a standard Normal distribution, and square each and add them, the sum of these will follow a chi-squared distribution with n degrees of freedom. This theoretical result is very useful and widely used in statistical testing […] The chi-squared distribution is always positive and its shape is uniquely determined by the degrees of freedom. The distribution becomes more symmetrical as the degrees of freedom increases. […] [The (noncentral) F distribution] is the distribution of the ratio of two chi-squared distributions and is used in hypothesis testing when we want to compare variances, such as in doing analysis of variance […] Sometimes data may follow a positively skewed distribution which becomes a Normal distribution when each data point is log-transformed [..] In this case the original data can be said to follow a lognormal distribution. The transformation of such data from log-normal to Normal is very useful in allowing skewed data to be analysed using methods based on the Normal distribution since these are usually more powerful than alternative methods”.

Half-Normal distribution.
Bivariate Normal distribution.
Negative binomial distribution.
Beta distribution.
Gamma distribution.
Conditional probability.
Bayes theorem.

April 26, 2018 Posted by | Books, Data, Mathematics, Medicine, Statistics | 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

Words

Most of the words below are words which I encountered while reading the books 100 cases in Surgery, The portable door, Expecting Someone Taller, and The Ionian Mission.

Hypernym/hyponym. Comminution. Scute. Introgression. Polysemous/polysemy. Flashover. Homophily. Opprobrious. Venturous. Remissive. Scuzzy. Funicular. Atelectasis. Valvulae conniventes. Haustrum/haustra. Anticlastic. Manubrium. Serpiginous. Trismus. Villagisation.

Bradawl. Barberry. Coppice. Squelch. Scry. Wodge. Graunch. Vergence. Encashment. Epitome. Crosspatch. Houndstooth. Bumf. Philter/philtre. Commemorative. Rapacious. Bisque. Mordant. Cochineal. Convocation.

Grobian. Cappabar/capperbar. Looby. Levanter. Vane. Circumambient. Shearwater. Scrove. Purcit. Opisthotonus. Slop. Dimity. Pinchbeck. Dactyl. Tramontane. Afflatus. Tamarisk. Pernicious. Coaming. Beylik.

Chrestomathy. Irade. Mastic. Levin. Mangonel. Uncovenanted. Theogony. Cruet. Emboss. Trafficator. Gymkhana. Martingale. Buddleia. Surcingle. Droopy. Nobble. Emery. Stemma. Wadi. Prosopography.

 

April 22, 2018 Posted by | Books, Language | Leave a comment

On the cryptographic hardness of finding a Nash equilibrium

I found it annoying that you generally can’t really hear the questions posed by the audience (which includes people like Avi Wigderson), especially considering that there are quite a few of these, especially in the middle section of the lecture. There are intermittent issues with the camera’s focus occasionally throughout the talk, but those are all transitory problems that should not keep you from watching the lecture. The sound issue at the beginning of the talk is resolved after 40 seconds.

One important take-away from this talk, if you choose not to watch it: “to date, there is no known efficient algorithm to find Nash equilibrium in games”. In general this paper – coauthored by the lecturer – seems from a brief skim to cover many of the topics also included in the lecture. I have added some other links to articles and topics covered/mentioned in the lecture below.

Nash’s Existence Theorem.
Reducibility Among Equilibrium Problems (Goldberg & Papadimitriou).
Three-Player Games Are Hard (Daskalakis & Papadimitriou).
3-Nash is PPAD-Complete (Chen & Deng).
PPAD (complexity).
NP-hardness.
On the (Im)possibility of Obfuscating Programs (Barak et al.).
On the Impossibility of Obfuscation with Auxiliary Input (Goldwasser & Kalai).
On Best-Possible Obfuscation (Goldwasser & Rothblum).
Functional Encryption without Obfuscation (Garg et al.).
On the Complexity of the Parity Argument and Other Inefficient Proofs of Existence (Papadimitriou).
Pseudorandom function family.
Revisiting the Cryptographic Hardness of Finding a Nash Equilibrium (Garg, Pandei & Srinivasan).
Constrained Pseudorandom Functions and Their Applications (Boneh & Waters).
Delegatable Pseudorandom Functions and Applications (Kiayias et al.).
Functional Signatures and Pseudorandom Functions (Boyle, Goldwasser & Ivan).
Universal Constructions and Robust Combiners for Indistinguishability Obfuscation and Witness Encryption (Ananth et al.).

April 18, 2018 Posted by | Computer science, Cryptography, Game theory, Lectures, Mathematics, Papers | 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

Medical Statistics (II)

In this post I’ll include some links and quotes related to topics covered in chapters 2 and 3 of the book. Chapter 2 is about ‘Collecting data’ and chapter 3 is about ‘Handling data: what steps are important?’

“Data collection is a key part of the research process, and the collection method will impact on later statistical analysis of the data. […] Think about the anticipated data analysis [in advance] so that data are collected in the appropriate format, e.g. if a mean will be needed for the analysis, then don’t record the data in categories, record the actual value. […] *It is useful to pilot the data collection process in a range of circumstances to make sure it will work in practice. *This usually involves trialling the data collection form on a smaller sample than intended for the study and enables problems with the data collection form to be identified and resolved prior to main data collection […] In general don’t expect the person filling out the form to do calculations as this may lead to errors, e.g. calculating a length of time between two dates. Instead, record each piece of information to allow computation of the particular value later […] The coding scheme should be designed at the same time as the form so that it can be built into the form. […] It may be important to distinguish between data that are simply missing from the original source and data that the data extractor failed to record. This can be achieved using different codes […] The use of numerical codes for non-numerical data may give the false impression that these data can be treated as if they were numerical data in the statistical analysis. This is not so.”

“It is critical that data quality is monitored and that this happens as the study progresses. It may be too late if problems are only discovered at the analysis stage. If checks are made during the data collection then problems can be corrected. More frequent checks may be worthwhile at the beginning of data collection when processes may be new and staff may be less experienced. […] The layout […] affects questionnaire completion rates and therefore impacts on the overall quality of the data collected.”

“Sometimes researchers need to develop a new measurement or questionnaire scale […] To do this rigorously requires a thorough process. We will outline the main steps here and note the most common statistical measures used in the process. […] Face validity *Is the scale measuring what it sets out to measure? […] Content validity *Does the scale cover all the relevant areas? […] *Between-observers consistency: is there agreement between different observers assessing the same individuals? *Within-observers consistency: is there agreement between assessments on the same individuals by the same observer on two different occasions? *Test-retest consistency: are assessments made on two separate occasions on the same individual similar? […] If a scale has several questions or items which all address the same issue then we usually expect each individual to get similar scores for those questions, i.e. we expect their responses to be internally consistent. […] Cronbach’s alpha […] is often used to assess the degree of internal consistency. [It] is calculated as an average of all correlations among the different questions on the scale. […] *Values are usually expected to be above 0.7 and below 0.9 *Alpha below 0.7 broadly indicates poor internal consistency *Alpha above 0.9 suggests that the items are very similar and perhaps fewer items could be used to obtain the same overall information”.

Bland–Altman plot.
Coefficient of variation.
Intraclass correlation.
Cohen’s kappa.
Likert scale. (“The key characteristic of Likert scales is that the scale is symmetrical. […] Care is needed when analyzing Likert scale data even though a numerical code is assigned to the responses, since the data are ordinal and discrete. Hence an average may be misleading […] It is quite common to collapse Likert scales into two or three categories such as agree versus disagree, but this has the disadvantage that data are discarded.”)
Visual analogue scale. (“VAS scores can be treated like continuous data […] Where it is feasible to use a VAS, it is preferable as it provides greater statistical power than a categorical scale”)

“Correct handling of data is essential to produce valid and reliable statistics. […] Data from research studies need to be coded […] It is important to document the coding scheme for categorical variables such as sex where it will not be obviously [sic, US] what the values mean […] It is strongly recommended that a unique numerical identifier is given to each subject, even if the research is conducted anonymously. […] Computerized datasets are often stored in a spreadsheet format with rows and columns of data. For most statistical analyses it is best to enter the data so that each row represents a different subject and each column a different variable. […] Prefixes or suffixes can be used to denote […] repeated measurements. If there are several repeated variables, use the same ‘scheme’ for all to avoid confusion. […] Try to avoid mixing suffixes and prefixes as it can cause confusion.”

“When data are entered onto a computer at different times it may be necessary to join datasets together. […] It is important to avoid over-writing a current dataset with a new updated version without keeping the old version as a separate file […] the two datasets must use exactly the same variable names for the same variables and the same coding. Any spelling mistakes will prevent a successful joining. […] It is worth checking that the joining has worked as expected by checking that the total number of observations in the updated file is the sum of the two previous files, and that the total number of variables is unchanged. […] When new data are collected on the same individuals at a later stage […], it may [again] be necessary to merge datasets. In order to do this the unique subject identifier must be used to identify the records that must be matched. For the merge to work, all variable names in the two datasets must be different except for the unique identifier. […] Spreadsheets are useful for entering and storing data. However, care should be taken when cutting and pasting different datasets to avoid misalignment of data. […] it is best not to join or sort datasets using a spreadsheet […in some research contexts, I’d add, this is also just plain impossible to even try, due to the amount of data involved – US…] […] It is important to ensure that a unique copy of the current file, the ‘master copy’, is stored at all times. Where the study involves more than one investigator, everyone needs to know who has responsibility for this. It is also important to avoid having two people revising the same file at the same time. […] It is important to keep a record of any changes that are made to the dataset and keep dated copies of datasets as changes are made […] Don’t overwrite datasets with edited versions as older versions may be needed later on.”

“Where possible, it is important to do some [data entry] checks early on to leave time for addressing problems while the study is in progress. […] *Check a random sample of forms for data entry accuracy. If this reveals problems then further checking may be needed. […] If feasible, consider checking data entry forms for key variables, e.g. the primary outcome. […] Range checks: […] tabulate all data to ensure there are no invalid values […] make sure responses are consistent with each other within subjects, e.g. check for any impossible or unlikely combination of responses such as a male with a pregnancy […] Check where feasible that any gaps are true gaps and not missed data entry […] Sometimes finding one error may lead to others being uncovered. For example, if a spreadsheet was used for data entry and one entry was missed, all following entries may be in the wrong columns. Hence, always consider if the discovery of one error may imply that there are others. […] Plots can be useful for checking larger datasets.”

Data monitoring committee.
Damocles guidelines.
Overview of stopping rules for clinical trials.
Pocock boundary.
Haybittle–Peto boundary.

“Trials are only stopped early when it is considered that the evidence for either benefit or harm is overwhelmingly strong. In such cases, the effect size will inevitably be larger than anticipated at the outset of the trial in order to trigger the early stop. Hence effect estimates from trials stopped early tend to be more extreme than would be the case if these trials had continued to the end, and so estimates of the efficacy or harm of a particular treatment may be exaggerated. This phenomenon has been demonstrated in recent reviews.1,2 […] Sometimes it becomes apparent part way through a trial that the assumptions made in the original sample size calculations are not correct. For example, where the primary outcome is a continuous variable, an estimate of the standard deviation (SD) is needed to calculate the required sample size. When the data are summarized during the trial, it may become apparent that the observed SD is different from that expected. This has implications for the statistical power. If the observed SD is smaller than expected then it may be reasonable to reduce the sample size but if it is bigger then it may be necessary to increase it.”

April 16, 2018 Posted by | Books, Medicine, Statistics | Leave a comment

100 cases in surgery (I)

We hope this book will give a good introduction to common surgical conditions seen in everyday surgical practice. Each question has been followed up with a brief overview of the condition and its immediate management. The book should act as an essential revision aid for surgical finals and as a basis for practising surgery after qualification.

This book is far from the first book I read in this series, and the format is the same as usual: There are 100 cases included, with a variety of different organ systems and diagnoses/settings encountered. The first page of a case presents a basic history and some key findings (lab tests, x-rays, results of imaging studies) and asks you a few questions about the case; the second and sometimes third page then provides answers to the questions and some important observations of note. Cases have of course been chosen in order to illustrate a wide variety of different medical scenarios involving many different organ systems and types of complaints. All cases are ‘to some extent’ surgical in nature, but in far from all cases will surgery necessarily be the required/indicated treatment option in the specific context; sometimes non-surgical management will be preferable, sometimes (much too often, in some oncological settings..) tumours are not resectable, some of the cases deal with complications to surgical procedures, etc.

The degree with which I was familiar with the topics covered in the book was highly variable; I’ve never really read any previous medical textbooks (…more or less-) exclusively devoted to surgical topics, but I have previously in a variety of contexts read about topics such as neurosurgery, cardiovascular surgery, and the recent endocrinology text of course covered surgical topics within this field in some detail; on the other hand my knowledge of (e.g.) otorhinolaryngology is, well, …limited. Part of my motivation for having a go at this book was precisely that my knowledge of the field of surgery felt a bit too fragmented (…and, in some cases, non-existent) even if I still didn’t feel like reading, say, an 800-page handbook like this one on these topics. Despite the more modest page-count of this book I would caution against thinking this is a particularly easy/fast read; there are a lot of cases and each of them has something to teach you – and as should also be easily inferred from the quote from the preface included above, this book is probably not readable if you don’t have some medical background of one kind or another (‘read fluent medical textbook’).

Below I have added some links to topics covered in the first half of the book, as well as a few observations from the coverage.

Abdominal hernias.
Appendicitis.
Large-bowel obstruction. Small-bowel obstruction.
Perianal abscess.
Malignant melanoma. (“Factors in the history that are suggestive of malignant change in a mole[:] *Change in surface *itching *increase in size/shape/thickness *Change in colour *bleeding/ulceration *brown/pink halo […] *enlarged local lymph nodes”)
Meckel’s diverticulum.
Rectal cancer. Colorectal Cancer. (“Colorectal cancer is the second commonest cancer causing death in the UK […]. Right-sided lesions can present with iron-deficiency anaemia, weight loss or a right iliac fossa mass. Lef-sided lesions present with alteration in bowel habit, rectal bleeding, or as an emergency with obstruction or perforation.”)
Sigmoid and cecal volvulus.
Anal fissure.
Diverticular disease.
Hemorrhoids.
Crohn Disease Pathology. (“Increasing frequency of stool, anorexia, low-grade fever, abdominal tenderness and anaemia suggest an inflammatory bowel disease. […] The initial management of uncomplicated Crohn’s disease should be medical.”)
Ulcerative colitis. (“Long-standing ulcerative colitis carries an approximate 3 per cent risk of malignant change after 10 years”).
Acute Cholecystitis and Biliary Colic. (“The majority of episodes of acute cholecystitis settle with analgesia and antibiotics.”)
Acute pancreatitis. (“Ranson’s criteria are used to grade the severity of alcoholic pancreatitis […] Each fulfilled criterion scores a point and the total indicates the severity. […] Estimates on mortality are based on the number of points scored: 0–2 = 2 per cent; 3–4 = 15 per cent; 5–6 = 40 per cent; >7 = 100 per cent. […] The aim of treatment is to halt the progression of local inflammation into systemic inflammation, which can result in multi-organ failure. Patients will often require nursing in a high-dependency or intensive care unit. They require prompt fluid resuscitation, a urinary catheter and central venous pressure monitoring. Early enteral feeding is advocated by some specialists. If there is evidence of sepsis, the patient should receive broad-spectrum antibiotics. […] patients should be managed aggressively”)
Ascending cholangitis.
Surgical Treatment of Perforated Peptic Ulcer.
Splenic rupture. Kehr’s sign.
Barrett’s esophagus. Peptic strictures of the esophagus. (“Proton pump inhibitors are effective in reducing stricture recurrence and in the treatment of Barrett’s oesophagus. If frequent dilatations are required despite acid suppression, then surgery should be considered. […] The risk of cancer is increased by up to 30 times in patients with Barrett’s oesophagus. If Barrett’s oesophagus is found at endoscopy, then the patient should be started on lifelong acid suppression. The patient should then have endoscopic surveillance to detect dysplasia before progression to carcinoma.”)
Esophageal Cancer. (“oesophageal carcinoma […] typically affects patients between 60 and 70 years of age and has a higher incidence in males. […] Dysphagia is the most common presenting symptom and is often associated with weight loss. […] Approximately 40 per cent of patients are suitable for surgical resection.”)
Pancreatic cancer. Courvoisier’s law. (“Pancreatic cancer classically presents with painless jaundice from biliary obstruction at the head of the pancreas and is associated with a distended gallbladder. Patients with pancreatic cancer can also present with epigastric pain, radiating through to the back, and vomiting due to duodenal obstruction. Pancreatic cancer occurs in patients between 60 and 80 years of age […] Roughly three-quarters have metastases at presentation […] Only approximately 15 per cent of pancreatic malignancies are surgically resectable.”)
Chronic pancreatitis. (“Chronic pancreatitis is an irreversible inflammation causing pancreatic fibrosis and calcification. Patients usually present with chronic abdominal pain and normal or mildly elevated pancreatic enzyme levels. The pancreas may have lost its endocrine and exocrine function, leading to diabetes mellitus and steatorrhea. […] The mean age of onset is 40 years, with a male preponderance of 4:1. […] thirty per cent of cases of chronic pancreatitis are idiopathic.”)
Myelofibrosis.
Gastric cancer. (“Gastric carcinoma is the second commonest cause of cancer worldwide. […] The highest incidence is in Eastern Asia, with a falling incidence in Western Europe. Diet and H. pylori infection are thought to be the two most important environmental factors in the development of gastric cancer. Diets rich in pickled vegetables, salted fish and smoked meats are thought to predispose to gastric cancer. […] Gastric cancer typically presents late and is associated with a poor prognosis. […] Surgical resection is not possible in the majority of patients.”)
Fibroadenomas of the breast. (“On examination, [benign fibroadenomas] tend to be spherical, smooth and sometimes lobulated with a rubbery consistency. The differential diagnosis includes fibrocystic disease (fluctuation in size with menstrual cycle and often associated with mild tenderness), a breast cyst (smooth, well-defined consistency like fibroadenoma but a hard as opposed to a rubbery consistency) or breast carcinoma (irregular, indistinct surface and shape with hard consistency).”)
Graves’ disease. (“Patients often present with many symptoms including palpitations, anxiety, thirst, sweating, weight loss, heat intolerance and increased bowel frequency. Enhanced activity of the adrenergic system also leads to agitation and restlessness. Approximately 25–30 per cent of patients with Graves’ disease have clinical evidence of ophthalmopathy. This almost only occurs in Graves’ disease (very rarely found in hypothyroidism)”)
Ruptured abdominal aortic aneurysm: a surgical emergency with many clinical presentations.
Temporal arteritis.
Transient ischemic attack. (“A stenosis of more than 70 per cent in the internal carotid artery is an indication for carotid endarterectomy in a patient with TIAs […]. The procedure should be carried out as soon as possible and within 2 weeks of the symptoms to prevent a major stroke.”)
Acute Mesenteric Ischemia.
Acute limb ischaemia. (“Signs and symptoms of acute limb ischaemia – the six Ps: •Pain •Pulseless •Pallor •Paraesthesia •Perishingly cold •Paralysis”).
Cervical rib.
Peripheral Arterial Occlusive Disease. (“The disease will only progress in one in four patients with intermittent claudication: therefore, unless the disease is very disabling for the patient, treatment is conservative. […] Investigations should include ankle–brachial pressure index (ABPI): this is typically <0.9 in patients with claudication; however, calcified vessels (typically in patients with diabetes) may result in an erroneously normal or high ABPI. […] Regular exercise has been shown to increase the claudication distance. In the minority of cases that do require intervention (i.e. severe short distance claudication not improving with exercise), angioplasty and bypass surgery are considered.”)
Venous ulcer. Marjolin’s ulcer. (“It is important to distinguish arterial from venous ulceration, as use of compression to treat the former type of ulcer is contraindicated.”)

April 14, 2018 Posted by | Books, Cancer/oncology, Gastroenterology, Medicine | Leave a comment

Structural engineering

“The purpose of the book is three-fold. First, I aim to help the general reader appreciate the nature of structure, the role of the structural engineer in man-made structures, and understand better the relationship between architecture and engineering. Second, I provide an overview of how structures work: how they stand up to the various demands made of them. Third, I give students and prospective students in engineering, architecture, and science access to perspectives and qualitative understanding of advanced modern structures — going well beyond the simple statics of most introductory texts. […] Structural engineering is an important part of almost all undergraduate courses in engineering. This book is novel in the use of ‘thought-experiments’ as a straightforward way of explaining some of the important concepts that students often find the most difficult. These include virtual work, strain energy, and maximum and minimum energy principles, all of which are basic to modern computational techniques. The focus is on gaining understanding without the distraction of mathematical detail. The book is therefore particularly relevant for students of civil, mechanical, aeronautical, and aerospace engineering but, of course, it does not cover all of the theoretical detail necessary for completing such courses.”

The above quote is from the book‘s preface. I gave the book 2 stars on goodreads, and I must say that I think David Muir Wood’s book in this series on a similar and closely overlapping topic, civil engineering, was just a significantly better book – if you’re planning on reading only one book on these topics, in my opinion you should pick Wood’s book. I have two main complaints against this book: There’s too much stuff about the aesthetic properties of structures, and the history- and development of the differences between architecture and engineering; and the author seems to think it’s no problem covering quite complicated topics with just analogies and thought experiments, without showing you any of the equations. As for the first point, I don’t really have any interest in aesthetics or architectural history; as for the second, I can handle math reasonably well, but I usually have trouble when people insist on hiding the equations from me and talking only ‘in images’. The absence of equations doesn’t mean the topic coverage is dumbed-down, much; it’s rather the case that the author is trying to cover the sort of material that we usually use mathematics to talk about, because this is the most efficient language to use, using different kinds of language; the problem is that things get lost in the translation. He got rid of the math, but not the complexity. The book does include many illustrations as well, including illustrations of some quite complicated topics and dynamics, but some of the things he talks about in the book are things you can’t illustrate well with images because you ‘run out of dimensions’ before you’ve handled all the relevant aspects/dynamics, an admission he himself makes in the book.

Anyway, the book is not terrible and there’s some interesting stuff in there. I’ve added a few more quotes and some links related to the book’s coverage below.

“All structures span a gap or a space of some kind and their primary role is to transmit the imposed forces safely. A bridge spans an obstruction like a road or a river. The roof truss of a house spans the rooms of the house. The fuselage of a jumbo jet spans between wheels of its undercarriage on the tarmac of an airport terminal and the self-weight, lift and drag forces in flight. The hull of a ship spans between the variable buoyancy forces caused by the waves of the sea. To be fit for purpose every structure has to cope with specific local conditions and perform inside acceptable boundaries of behaviour—which engineers call ‘limit states’. […] Safety is paramount in two ways. First, the risk of a structure totally losing its structural integrity must be very low—for example a building must not collapse or a ship break up. This maximum level of performance is called an ultimate limit state. If a structure should reach that state for whatever reason then the structural engineer tries to ensure that the collapse or break up is not sudden—that there is some degree of warning—but this is not always possible […] Second, structures must be able to do what they were built for—this is called serviceability or performance limit state. So for example a skyscraper building must not sway so much that it causes discomfort to the occupants, even if the risk of total collapse is still very small.”

“At its simplest force is a pull (tension) or a push (compression). […] There are three ways in which materials are strong in different combinations—pulling (tension), pushing (compression), and sliding (shear). Each is very important […] all intact structures have internal forces that balance the external forces acting on them. These external forces come from simple self-weight, people standing, sitting, walking, travelling across them in cars, trucks, and trains, and from the environment such as wind, water, and earthquakes. In that state of equilibrium it turns out that structures are naturally lazy—the energy stored in them is a minimum for that shape or form of structure. Form-finding structures are a special group of buildings that are allowed to find their own shape—subject to certain constraints. There are two classes—in the first, the form-finding process occurs in a model (which may be physical or theoretical) and the structure is scaled up from the model. In the second, the structure is actually built and then allowed to settle into shape. In both cases the structures are self-adjusting in that they move to a position in which the internal forces are in equilibrium and contain minimum energy. […] there is a big problem in using self-adjusting structures in practice. The movements under changing loads can make the structures unfit for purpose. […] Triangles are important in structural engineering because they are the simplest stable form of structure and you see them in all kinds of structures—whether form-finding or not. […] Other forms of pin jointed structure, such as a rectangle, will deform in shear as a mechanism […] unless it has diagonal bracing—making it triangular. […] bending occurs in part of a structure when the forces acting on it tend to make it turn or rotate—but it is constrained or prevented from turning freely by the way it is connected to the rest of the structure or to its foundations. The turning forces may be internal or external.”

“Energy is the capacity of a force to do work. If you stretch an elastic band it has an internal tension force resisting your pull. If you let go of one end the band will recoil and could inflict a sharp sting on your other hand. The internal force has energy or the capacity to do work because you stretched it. Before you let go the energy was potential; after you let go the energy became kinetic. Potential energy is the capacity to do work because of the position of something—in this case because you pulled the two ends of the band apart. […] A car at the top of a hill has the potential energy to roll down the hill if the brakes are released. The potential energy in the elastic band and in a structure has a specific name—it is called ‘strain energy’. Kinetic energy is due to movement, so when you let go of the band […] the potential energy is converted into kinetic energy. Kinetic energy depends on mass and velocity—so a truck can develop more kinetic energy than a small car. When a structure is loaded by a force then the structure moves in whatever way it can to ‘get out of the way’. If it can move freely it will do—just as if you push a car with the handbrake off it will roll forward. However, if the handbrake is on the car will not move, and an internal force will be set up between the point at which you are pushing and the wheels as they grip the road.”

“[A] rope hanging freely as a catenary has minimum energy and […] it can only resist one kind of force—tension. Engineers say that it has one degree of freedom. […] In brief, degrees of freedom are the independent directions in which a structure or any part of a structure can move or deform […] Movements along degrees of freedom define the shape and location of any object at a given time. Each part, each piece of a physical structure whatever its size is a physical object embedded in and connected to other objects […] similar objects which I will call its neighbours. Whatever its size each has the potential to move unless something stops it. Where it may move freely […] then no internal resisting force is created. […] where it is prevented from moving in any direction a reaction force is created with consequential internal forces in the structure. For example at a support to a bridge, where the whole bridge is normally stopped from moving vertically, then an external vertical reaction force develops which must be resisted by a set of internal forces that will depend on the form of the bridge. So inside the bridge structure each piece, however small or large, will move—but not freely. The neighbouring objects will get in the way […]. When this happens internal forces are created as the objects bump up against each other and we represent or model those forces along the pathways which are the local degrees of freedom. The structure has to be strong enough to resist these internal forces along these pathways.”

“The next question is ‘How do we find out how big the forces and movements are?’ It turns out that there is a whole class of structures where this is reasonably straightforward and these are the structures covered in elementary textbooks. Engineers call them ‘statically determinate’ […] For these structures we can find the sizes of the forces just by balancing the internal and external forces to establish equilibrium. […] Unfortunately many real structures can’t be fully explained in this way—they are ‘statically indeterminate‘. This is because whilst establishing equilibrium between internal and external forces is necessary it is not sufficient for finding all of the internal forces. […] The four-legged stool is statically indeterminate. You will begin to understand this if you have ever sat at a fourlegged wobbly table […] which has one leg shorter than the other three legs. There can be no force in that leg because there is no reaction from the ground. What is more, the opposite leg will have no internal force either because otherwise there would be a net turning moment about the line joining the other two legs. Thus the table is balanced on two legs—which is why it wobbles back and forth. […] each leg has one degree of freedom but we have only three ways of balancing them in the (x,y,z) directions. In mathematical terms, we have four unknown  variables (the internal forces) but only three equations (balancing equilibrium in three directions). It follows that there isn’t just one set of forces in equilibrium—indeed, there are many such sets.”

“[W]hen a structure is in equilibrium it has minimum strain energy. […] Strictly speaking, minimum strain energy as a criterion for equilibrium is [however] true only in specific circumstances. To understand this we need to look at the constitutive relations between forces and deformations or displacements. Strain energy is stored potential energy and that energy is the capacity to do work. The strain energy in a body is there because work has been done on it—a force moved through a distance. Hence in order to know the energy we must know how much displacement is caused by a given force. This is called a ‘constitutive relation’ and has the form ‘force equals a constitutive factor times a displacement’. The most common of these relationships is called ‘linear elastic’ where the force equals a simple numerical factor—called the stiffness—times the displacement […] The inverse of the stiffness is called flexibility”.

“Aeroplanes take off or ascend because the lift forces due to the forward motion of the plane exceed the weight […] In level flight or cruise the plane is neutrally buoyant and flies at a steady altitude. […] The structure of an aircraft consists of four sets of tubes: the fuselage, the wings, the tail, and the fin. For obvious reasons their weight needs to be as small as possible. […] Modern aircraft structures are semi-monocoque—meaning stressed skin but with a supporting frame. In other words the skin covering, which may be only a few millimetres thick, becomes part of the structure. […] In an overall sense, the lift and drag forces effectively act on the wings through centres of pressure. The wings also carry the weight of engines and fuel. During a typical flight, the positions of these centres of force vary along the wing—for example as fuel is used. The wings are balanced cantilevers fixed to the fuselage. Longer wings (compared to their width) produce greater lift but are also necessarily heavier—so a compromise is required.”

“When structures move quickly, in particular if they accelerate or decelerate, we have to consider […] the inertia force and the damping force. They occur, for example, as an aeroplane takes off and picks up speed. They occur in bridges and buildings that oscillate in the wind. As these structures move the various bits of the structure remain attached—perhaps vibrating in very complex patterns, but they remain joined together in a state of dynamic equilibrium. An inertia force results from an acceleration or deceleration of an object and is directly proportional to the weight of that object. […] Newton’s 2nd Law tells us that the magnitudes of these [inertial] forces are proportional to the rates of change of momentum. […] Damping arises from friction or ‘looseness’ between components. As a consequence, energy is dissipated into other forms such as heat and sound, and the vibrations get smaller. […] The kinetic energy of a structure in static equilibrium is zero, but as the structure moves its potential energy is converted into kinetic energy. This is because the total energy remains constant by the principle of the conservation of energy (the first law of thermodynamics). The changing forces and displacements along the degree of freedom pathways travel as a wave […]. The amplitude of the wave depends on the nature of the material and the connections between components.”

“For [a] structure to be safe the materials must be strong enough to resist the tension, the compression, and the shear. The strength of materials in tension is reasonably straightforward. We just need to know the limiting forces the material can resist. This is usually specified as a set of stresses. A stress is a force divided by a cross sectional area and represents a localized force over a small area of the material. Typical limiting tensile stresses are called the yield stress […] and the rupture stress—so we just need to know their numerical values from tests. Yield occurs when the material cannot regain its original state, and permanent displacements or strains occur. Rupture is when the material breaks or fractures. […] Limiting average shear stresses and maximum allowable stress are known for various materials. […] Strength in compression is much more difficult […] Modern practice using the finite element method enables us to make theoretical estimates […] but it is still approximate because of the simplifications necessary to do the computer analysis […]. One of the challenges to engineers who rely on finite element analysis is to make sure they understand the implications of the simplifications used.”

“Dynamic loads cause vibrations. One particularly dangerous form of vibration is called resonance […]. All structures have a natural frequency of free vibration. […] Resonance occurs if the frequency of an external vibrating force coincides with the natural frequency of the structure. The consequence is a rapid build up of vibrations that can become seriously damaging. […] Wind is a major source of vibrations. As it flows around a bluff body the air breaks away from the surface and moves in a circular motion like a whirlpool or whirlwind as eddies or vortices. Under certain conditions these vortices may break away on alternate sides, and as they are shed from the body they create pressure differences that cause the body to oscillate. […] a structure is in stable equilibrium when a small perturbation does not result in large displacements. A structure in dynamic equilibrium may oscillate about a stable equilibrium position. […] Flutter is dynamic and a form of wind-excited self-reinforcing oscillation. It occurs, as in the P-delta effect, because of changes in geometry. Forces that are no longer in line because of large displacements tend to modify those displacements of the structure, and these, in turn, modify the forces, and so on. In this process the energy input during a cycle of vibration may be greater than that lost by damping and so the amplitude increases in each cycle until destruction. It is a positive feed-back mechanism that amplifies the initial deformations, causes non-linearity, material plasticity and decreased stiffness, and reduced natural frequency. […] Regular pulsating loads, even very small ones, can cause other problems too through a phenomenon known as fatigue. The word is descriptive—under certain conditions the materials just get tired and crack. A normally ductile material like steel becomes brittle. Fatigue occurs under very small loads repeated many millions of times. All materials in all types of structures have a fatigue limit. […] Fatigue damage occurs deep in the material as microscopic bonds are broken. The problem is particularly acute in the heat affected zones of welded structures.”

“Resilience is the ability of a system to recover quickly from difficult conditions. […] One way of delivering a degree of resilience is to make a structure fail-safe—to mitigate failure if it happens. A household electrical fuse is an everyday example. The fuse does not prevent failure, but it does prevent extreme consequences such as an electrical fire. Damage-tolerance is a similar concept. Damage is any physical harm that reduces the value of something. A damage-tolerant structure is one in which any damage can be accommodated at least for a short time until it can be dealt with. […] human factors in failure are not just a matter of individuals’ slips, lapses, or mistakes but are also the result of organizational and cultural situations which are not easy to identify in advance or even at the time. Indeed, they may only become apparent in hindsight. It follows that another major part of safety is to design a structure so that it can be inspected, repaired, and maintained. Indeed all of the processes of creating a structure, whether conceiving, designing, making, or monitoring performance, have to be designed with sufficient resilience to accommodate unexpected events. In other words, safety is not something a system has (a property), rather it is something a system does (a performance). Providing resilience is a form of control—a way of managing uncertainties and risks.”

Stiffness.
Antoni Gaudí. Heinz Isler. Frei Otto.
Eden Project.
Tensegrity.
Bending moment.
Shear and moment diagram.
Stonehenge.
Pyramid at Meidum.
Vitruvius.
Master builder.
John Smeaton.
Puddling (metallurgy).
Cast iron.
Isambard Kingdom Brunel.
Henry Bessemer. Bessemer process.
Institution of Structural Engineers.
Graphic statics (wiki doesn’t have an article on this topic under this name and there isn’t much here, but it looks like google has a lot if you’re interested).
Constitutive equation.
Deformation (mechanics).
Compatibility (mechanics).
Principle of Minimum Complementary Energy.
Direct stiffness method. Finite element method.
Hogging and sagging.
Centre of buoyancy. Metacentre (fluid mechanics). Angle of attack.
Box girder bridge.
D’Alembert’s principle.
Longeron.
Buckling.
S-n diagram.

April 11, 2018 Posted by | Books, Engineering, Physics | Leave a comment

Medical Statistics (I)

I was more than a little critical of the book in my review on goodreads, and the review is sufficiently detailed that I thought it would be worth including it in this post. Here’s what I wrote on goodreads (slightly edited to take full advantage of the better editing options on wordpress):

“The coverage is excessively focused on significance testing. The book also provides very poor coverage of model selection topics, where the authors not once but repeatedly recommend employing statistically invalid approaches to model selection (the authors recommend using hypothesis testing mechanisms to guide model selection, as well as using adjusted R-squared for model selection decisions – both of which are frankly awful ideas, for reasons which are obvious to people familiar with the field of model selection. “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.” “While adjusted R2 is useful as a descriptive statistic, it is not useful in model selection” – quotes taken directly from Burnham & Anderson’s book Model Selection and Multi-Model Inference: A Practical Information-Theoretic Approach).

The authors do not at any point in the coverage even mention the option of using statistical information criteria to guide model selection decisions, and frankly repeatedly recommend doing things which are known to be deeply problematic. The authors also cover material from Borenstein and Hedges’ meta-analysis text in the book, yet still somehow manage to give poor advice in the context of meta-analysis along similar lines (implicitly advising people to base model decisions within the context of whether to use fixed effects or random effects on the results of heterogeneity tests, despite this approach being criticized as problematic in the formerly mentioned text).

Basic and not terrible, but there are quite a few problems with this text.”

I’ll add a few more details about the above-mentioned problems before moving on to the main coverage. As for the model selection topic I refer specifically to my coverage of Burnham and Anderson’s book here and here – these guys spent a lot of pages talking about why you shouldn’t do what the authors of this book recommend, and I’m sort of flabbergasted medical statisticians don’t know this kind of stuff by now. To people who’ve read both these books, it’s not really in question who’s in the right here.

I believe part of the reason why I was very annoyed at the authors at times was that they seem to promote exactly a sort of blind unthinking hypothesis-testing approach to things that is unfortunately very common – the entire book is saturated with hypothesis testing stuff, which means that many other topics are woefully insufficiently covered. The meta-analysis example is probably quite illustrative; the authors spend multiple pages on study heterogeneity and how to deal with it, but the entire coverage there is centered around the discussion of a most-likely underpowered test, the result of which should perhaps in the best case scenario direct the researcher’s attention to topics he should be have been thinking carefully about from the very start of his data analysis. You don’t need to quote many words from Borenstein and Hedges (here’s a relevant link) to get to the heart of the matter here:

“It makes sense to use the fixed-effect model if two conditions are met. First, we believe that all the studies included in the analysis are functionally identical. Second, our goal is to compute the common effect size for the identified population, and not to generalize to other populations. […] this situation is relatively rare. […] By contrast, when the researcher is accumulating data from a series of studies that had been performed by researchers operating independently, it would be unlikely that all the studies were functionally equivalent. Typically, the subjects or interventions in these studies would have differed in ways that would have impacted on the results, and therefore we should not assume a common effect size. Therefore, in these cases the random-effects model is more easily justified than the fixed-effect model.

A report should state the computational model used in the analysis and explain why this model was selected. A common mistake is to use the fixed-effect model on the basis that there is no evidence of heterogeneity. As [already] explained […], the decision to use one model or the other should depend on the nature of the studies, and not on the significance of this test [because the test will often have low power anyway].”

Yet these guys spend their efforts here talking about a test that is unlikely to yield useful information and which if anything probably distracts the reader from the main issues at hand; are the studies functionally equivalent? Do we assume there’s one (‘true’) effect size, or many? What do those coefficients we’re calculating actually mean? The authors do in fact include a lot of cautionary notes about how to interpret the test, but in my view all this means is that they’re devoting critical pages to peripheral issues – and perhaps even reinforcing the view that the test is important, or why else would they spend so much effort on it? – rather than promote good thinking about the key topics at hand.

Anyway, enough of the critical comments. Below a few links related to the first chapter of the book, as well as some quotes.

Declaration of Helsinki.
Randomized controlled trial.
Minimization (clinical trials).
Blocking (statistics).
Informed consent.
Blinding (RCTs). (…related xkcd link).
Parallel study. Crossover trial.
Zelen’s design.
Superiority, equivalence, and non-inferiority trials.
Intention-to-treat concept: A review.
Case-control study. Cohort study. Nested case-control study. Cross-sectional study.
Bradford Hill criteria.
Research protocol.
Sampling.
Type 1 and type 2 errors.
Clinical audit. A few quotes on this topic:

“‘Clinical audit’ is a quality improvement process that seeks to improve the patient care and outcomes through systematic review of care against explicit criteria and the implementation of change. Aspects of the structures, processes and outcomes of care are selected and systematically evaluated against explicit criteria. […] The aim of audit is to monitor clinical practice against agreed best practice standards and to remedy problems. […] the choice of topic is guided by indications of areas where improvement is needed […] Possible topics [include] *Areas where a problem has been identified […] *High volume practice […] *High risk practice […] *High cost […] *Areas of clinical practice where guidelines or firm evidence exists […] The organization carrying out the audit should have the ability to make changes based on their findings. […] In general, the same methods of statistical analysis are used for audit as for research […] The main difference between audit and research is in the aim of the study. A clinical research study aims to determine what practice is best, whereas an audit checks to see that best practice is being followed.”

A few more quotes from the end of the chapter:

“In clinical medicine and in medical research it is fairly common to categorize a biological measure into two groups, either to aid diagnosis or to classify an outcome. […] It is often useful to categorize a measurement in this way to guide decision-making, and/or to summarize the data but doing this leads to a loss of information which in turn has statistical consequences. […] If a continuous variable is used for analysis in a research study, a substantially smaller sample size will be needed than if the same variable is categorized into two groups […] *Categorization of a continuous variable into two groups loses much data and should be avoided whenever possible *Categorization of a continuous variable into several groups is less problematic”

“Research studies require certain specific data which must be collected to fulfil the aims of the study, such as the primary and secondary outcomes and main factors related to them. Beyond these data there are often other data that could be collected and it is important to weigh the costs and consequences of not collecting data that will be needed later against the disadvantages of collecting too much data. […] collecting too much data is likely to add to the time and cost to data collection and processing, and may threaten the completeness and/or quality of all of the data so that key data items are threatened. For example if a questionnaire is overly long, respondents may leave some questions out or may refuse to fill it out at all.”

Stratified samples are used when fixed numbers are needed from particular sections or strata of the population in order to achieve balance across certain important factors. For example a study designed to estimate the prevalence of diabetes in different ethnic groups may choose a random sample with equal numbers of subjects in each ethnic group to provide a set of estimates with equal precision for each group. If a simple random sample is used rather than a stratified sample, then estimates for minority ethnic groups may be based on small numbers and have poor precision. […] Cluster samples may be chosen where individuals fall naturally into groups or clusters. For example, patients on a hospital wards or patients in a GP practice. If a sample is needed of these patients, it may be easier to list the clusters and then to choose a random sample of clusters, rather than to choose a random sample of the whole population. […] Cluster sampling is less efficient statistically than simple random sampling […] the ICC summarizes the extent of the ‘clustering effect’. When individuals in the same cluster are much more alike than individuals in different clusters with respect to an outcome, then the clustering effect is greater and the impact on the required sample size is correspondingly greater. In practice there can be a substantial effect on the sample size even when the ICC is quite small. […] As well as considering how representative a sample is, it is important […] to consider the size of the sample. A sample may be unbiased and therefore representative, but too small to give reliable estimates. […] Prevalence estimates from small samples will be imprecise and therefore may be misleading. […] The greater the variability of a measure, the greater the number of subjects needed in the sample to estimate it precisely. […] the power of a study is the ability of the study to detect a difference if one exists.”

April 9, 2018 Posted by | Books, Epidemiology, Medicine, Statistics | Leave a comment

Words

Most of the words below are words which I encountered while reading the books The Fortune of War, The Surgeon’s Mate, In Your Dreams, and Who’s Afraid of Beowulf.

Pervenche. Intromit. Subfusc. Inspissated. Supple. Ukase. Commensal. Croft. Scantling. Compendious. Nympholept. Forfantery (an unsual – but very useful – link, for an unusual word). Trunnion. Hominy. Slubberdegullion. Lickerish. Brail. Grapnel. Swingle. Altumal.

Éclaircissement. Costiveness. Vang. Heady. Mort. Cingulum. Swingeing. Avifauna. Carminative. Accoucheur. Peccavi. Grommet. Woolding. Scow. Gibbous. Tierce. Burgoo. Tye. Inclement. Lobscouse.

Irrefragable. Gurnard. Bilaterian. Malmsey. Corbel. Jakes. Bonnet. Doddle. Rock dash. Purlin. Pillock. Graunch. Chirrup. Skive. Pelmet. Feckless. Pedalo. Howe. Tannin. Garnet.

Delate. Derisory. Saveloy. Flan. Quillon. Corvid. Hierophant. Thane. Laconic. Chthonic. Cowrie. Repique. Broch. Cheep. Carborundum. Shieling. Bothy. Meronymy. Meronomy. Mereology.

 

April 5, 2018 Posted by | Books, Language | Leave a comment

Networks

I actually think this was a really nice book, considering the format – I gave it four stars on goodreads. One of the things I noticed people didn’t like about it in the reviews is that it ‘jumps’ a bit in terms of topic coverage; it covers a wide variety of applications and analytical settings. I mostly don’t consider this a weakness of the book – even if occasionally it does get a bit excessive – and I can definitely understand the authors’ choice of approach; it’s sort of hard to illustrate the potential the analytical techniques described within this book have if you’re not allowed to talk about all the areas in which they have been – or could be gainfully – applied. A related point is that many people who read the book might be familiar with the application of these tools in specific contexts but have perhaps not thought about the fact that similar methods are applied in many other areas (and they might all of them be a bit annoyed the authors don’t talk more about computer science applications, or foodweb analyses, or infectious disease applications, or perhaps sociometry…). Most of the book is about graph-theory-related stuff, but a very decent amount of the coverage deals with applications, in a broad sense of the word at least, not theory. The discussion of theoretical constructs in the book always felt to me driven to a large degree by their usefulness in specific contexts.

I have covered related topics before here on the blog, also quite recently – e.g. there’s at least some overlap between this book and Holland’s book about complexity theory in the same series (I incidentally think these books probably go well together) – and as I found the book slightly difficult to blog as it was I decided against covering it in as much detail as I sometimes do when covering these texts – this means that I decided to leave out the links I usually include in posts like these.

Below some quotes from the book.

“The network approach focuses all the attention on the global structure of the interactions within a system. The detailed properties of each element on its own are simply ignored. Consequently, systems as different as a computer network, an ecosystem, or a social group are all described by the same tool: a graph, that is, a bare architecture of nodes bounded by connections. […] Representing widely different systems with the same tool can only be done by a high level of abstraction. What is lost in the specific description of the details is gained in the form of universality – that is, thinking about very different systems as if they were different realizations of the same theoretical structure. […] This line of reasoning provides many insights. […] The network approach also sheds light on another important feature: the fact that certain systems that grow without external control are still capable of spontaneously developing an internal order. […] Network models are able to describe in a clear and natural way how self-organization arises in many systems. […] In the study of complex, emergent, and self-organized systems (the modern science of complexity), networks are becoming increasingly important as a universal mathematical framework, especially when massive amounts of data are involved. […] networks are crucial instruments to sort out and organize these data, connecting individuals, products, news, etc. to each other. […] While the network approach eliminates many of the individual features of the phenomenon considered, it still maintains some of its specific features. Namely, it does not alter the size of the system — i.e. the number of its elements — or the pattern of interaction — i.e. the specific set of connections between elements. Such a simplified model is nevertheless enough to capture the properties of the system. […] The network approach [lies] somewhere between the description by individual elements and the description by big groups, bridging the two of them. In a certain sense, networks try to explain how a set of isolated elements are transformed, through a pattern of interactions, into groups and communities.”

“[T]he random graph model is very important because it quantifies the properties of a totally random network. Random graphs can be used as a benchmark, or null case, for any real network. This means that a random graph can be used in comparison to a real-world network, to understand how much chance has shaped the latter, and to what extent other criteria have played a role. The simplest recipe for building a random graph is the following. We take all the possible pair of vertices. For each pair, we toss a coin: if the result is heads, we draw a link; otherwise we pass to the next pair, until all the pairs are finished (this means drawing the link with a probability p = ½, but we may use whatever value of p). […] Nowadays [the random graph model] is a benchmark of comparison for all networks, since any deviations from this model suggests the presence of some kind of structure, order, regularity, and non-randomness in many real-world networks.”

“…in networks, topology is more important than metrics. […] In the network representation, the connections between the elements of a system are much more important than their specific positions in space and their relative distances. The focus on topology is one of its biggest strengths of the network approach, useful whenever topology is more relevant than metrics. […] In social networks, the relevance of topology means that social structure matters. […] Sociology has classified a broad range of possible links between individuals […]. The tendency to have several kinds of relationships in social networks is called multiplexity. But this phenomenon appears in many other networks: for example, two species can be connected by different strategies of predation, two computers by different cables or wireless connections, etc. We can modify a basic graph to take into account this multiplexity, e.g. by attaching specific tags to edges. […] Graph theory [also] allows us to encode in edges more complicated relationships, as when connections are not reciprocal. […] If a direction is attached to the edges, the resulting structure is a directed graph […] In these networks we have both in-degree and out-degree, measuring the number of inbound and outbound links of a node, respectively. […] in most cases, relations display a broad variation or intensity [i.e. they are not binary/dichotomous]. […] Weighted networks may arise, for example, as a result of different frequencies of interactions between individuals or entities.”

“An organism is […] the outcome of several layered networks and not only the deterministic result of the simple sequence of genes. Genomics has been joined by epigenomics, transcriptomics, proteomics, metabolomics, etc., the disciplines that study these layers, in what is commonly called the omics revolution. Networks are at the heart of this revolution. […] The brain is full of networks where various web-like structures provide the integration between specialized areas. In the cerebellum, neurons form modules that are repeated again and again: the interaction between modules is restricted to neighbours, similarly to what happens in a lattice. In other areas of the brain, we find random connections, with a more or less equal probability of connecting local, intermediate, or distant neurons. Finally, the neocortex — the region involved in many of the higher functions of mammals — combines local structures with more random, long-range connections. […] typically, food chains are not isolated, but interwoven in intricate patterns, where a species belongs to several chains at the same time. For example, a specialized species may predate on only one prey […]. If the prey becomes extinct, the population of the specialized species collapses, giving rise to a set of co-extinctions. An even more complicated case is where an omnivore species predates a certain herbivore, and both eat a certain plant. A decrease in the omnivore’s population does not imply that the plant thrives, because the herbivore would benefit from the decrease and consume even more plants. As more species are taken into account, the population dynamics can become more and more complicated. This is why a more appropriate description than ‘foodchains’ for ecosystems is the term foodwebs […]. These are networks in which nodes are species and links represent relations of predation. Links are usually directed (big fishes eat smaller ones, not the other way round). These networks provide the interchange of food, energy, and matter between species, and thus constitute the circulatory system of the biosphere.”

“In the cell, some groups of chemicals interact only with each other and with nothing else. In ecosystems, certain groups of species establish small foodwebs, without any connection to external species. In social systems, certain human groups may be totally separated from others. However, such disconnected groups, or components, are a strikingly small minority. In all networks, almost all the elements of the systems take part in one large connected structure, called a giant connected component. […] In general, the giant connected component includes not less than 90 to 95 per cent of the system in almost all networks. […] In a directed network, the existence of a path from one node to another does not guarantee that the journey can be made in the opposite direction. Wolves eat sheep, and sheep eat grass, but grass does not eat sheep, nor do sheep eat wolves. This restriction creates a complicated architecture within the giant connected component […] according to an estimate made in 1999, more than 90 per cent of the WWW is composed of pages connected to each other, if the direction of edges is ignored. However, if we take direction into account, the proportion of nodes mutually reachable is only 24 per cent, the giant strongly connected component. […] most networks are sparse, i.e. they tend to be quite frugal in connections. Take, for example, the airport network: the personal experience of every frequent traveller shows that direct flights are not that common, and intermediate stops are necessary to reach several destinations; thousands of airports are active, but each city is connected to less than 20 other cities, on average. The same happens in most networks. A measure of this is given by the mean number of connection of their nodes, that is, their average degree.”

“[A] puzzling contradiction — a sparse network can still be very well connected — […] attracted the attention of the Hungarian mathematicians […] Paul Erdős and Alfréd Rényi. They tackled it by producing different realizations of their random graph. In each of them, they changed the density of edges. They started with a very low density: less than one edge per node. It is natural to expect that, as the density increases, more and more nodes will be connected to each other. But what Erdős and Rényi found instead was a quite abrupt transition: several disconnected components coalesced suddenly into a large one, encompassing almost all the nodes. The sudden change happened at one specific critical density: when the average number of links per node (i.e. the average degree) was greater than one, then the giant connected component suddenly appeared. This result implies that networks display a very special kind of economy, intrinsic to their disordered structure: a small number of edges, even randomly distributed between nodes, is enough to generate a large structure that absorbs almost all the elements. […] Social systems seem to be very tightly connected: in a large enough group of strangers, it is not unlikely to find pairs of people with quite short chains of relations connecting them. […] The small-world property consists of the fact that the average distance between any two nodes (measured as the shortest path that connects them) is very small. Given a node in a network […], few nodes are very close to it […] and few are far from it […]: the majority are at the average — and very short — distance. This holds for all networks: starting from one specific node, almost all the nodes are at very few steps from it; the number of nodes within a certain distance increases exponentially fast with the distance. Another way of explaining the same phenomenon […] is the following: even if we add many nodes to a network, the average distance will not increase much; one has to increase the size of a network by several orders of magnitude to notice that the paths to new nodes are (just a little) longer. The small-world property is crucial to many network phenomena. […] The small-world property is something intrinsic to networks. Even the completely random Erdős-Renyi graphs show this feature. By contrast, regular grids do not display it. If the Internet was a chessboard-like lattice, the average distance between two routers would be of the order of 1,000 jumps, and the Net would be much slower [the authors note elsewhere that “The Internet is composed of hundreds of thousands of routers, but just about ten ‘jumps’ are enough to bring an information packet from one of them to any other.”] […] The key ingredient that transforms a structure of connections into a small world is the presence of a little disorder. No real network is an ordered array of elements. On the contrary, there are always connections ‘out of place’. It is precisely thanks to these connections that networks are small worlds. […] Shortcuts are responsible for the small-world property in many […] situations.”

“Body size, IQ, road speed, and other magnitudes have a characteristic scale: that is, an average value that in the large majority of cases is a rough predictor of the actual value that one will find. […] While height is a homogeneous magnitude, the number of social connection[s] is a heterogeneous one. […] A system with this feature is said to be scale-free or scale-invariant, in the sense that it does not have a characteristic scale. This can be rephrased by saying that the individual fluctuations with respect to the average are too large for us to make a correct prediction. […] In general, a network with heterogeneous connectivity has a set of clear hubs. When a graph is small, it is easy to find whether its connectivity is homogeneous or heterogeneous […]. In the first case, all the nodes have more or less the same connectivity, while in the latter it is easy to spot a few hubs. But when the network to be studied is very big […] things are not so easy. […] the distribution of the connectivity of the nodes of the […] network […] is the degree distribution of the graph. […] In homogeneous networks, the degree distribution is a bell curve […] while in heterogeneous networks, it is a power law […]. The power law implies that there are many more hubs (and much more connected) in heterogeneous networks than in homogeneous ones. Moreover, hubs are not isolated exceptions: there is a full hierarchy of nodes, each of them being a hub compared with the less connected ones.”

“Looking at the degree distribution is the best way to check if a network is heterogeneous or not: if the distribution is fat tailed, then the network will have hubs and heterogeneity. A mathematically perfect power law is never found, because this would imply the existence of hubs with an infinite number of connections. […] Nonetheless, a strongly skewed, fat-tailed distribution is a clear signal of heterogeneity, even if it is never a perfect power law. […] While the small-world property is something intrinsic to networked structures, hubs are not present in all kind of networks. For example, power grids usually have very few of them. […] hubs are not present in random networks. A consequence of this is that, while random networks are small worlds, heterogeneous ones are ultra-small worlds. That is, the distance between their vertices is relatively smaller than in their random counterparts. […] Heterogeneity is not equivalent to randomness. On the contrary, it can be the signature of a hidden order, not imposed by a top-down project, but generated by the elements of the system. The presence of this feature in widely different networks suggests that some common underlying mechanism may be at work in many of them. […] the Barabási–Albert model gives an important take-home message. A simple, local behaviour, iterated through many interactions, can give rise to complex structures. This arises without any overall blueprint”.

Homogamy, the tendency of like to marry like, is very strong […] Homogamy is a specific instance of homophily: this consists of a general trend of like to link to like, and is a powerful force in shaping social networks […] assortative mixing [is] a special form of homophily, in which nodes tend to connect with others that are similar to them in the number of connections. By contrast [when] high- and low-degree nodes are more connected to each other [it] is called disassortative mixing. Both cases display a form of correlation in the degrees of neighbouring nodes. When the degrees of neighbours are positively correlated, then the mixing is assortative; when negatively, it is disassortative. […] In random graphs, the neighbours of a given node are chosen completely at random: as a result, there is no clear correlation between the degrees of neighbouring nodes […]. On the contrary, correlations are present in most real-world networks. Although there is no general rule, most natural and technological networks tend to be disassortative, while social networks tend to be assortative. […] Degree assortativity and disassortativity are just an example of the broad range of possible correlations that bias how nodes tie to each other.”

“[N]etworks (neither ordered lattices nor random graphs), can have both large clustering and small average distance at the same time. […] in almost all networks, the clustering of a node depends on the degree of that node. Often, the larger the degree, the smaller the clustering coefficient. Small-degree nodes tend to belong to well-interconnected local communities. Similarly, hubs connect with many nodes that are not directly interconnected. […] Central nodes usually act as bridges or bottlenecks […]. For this reason, centrality is an estimate of the load handled by a node of a network, assuming that most of the traffic passes through the shortest paths (this is not always the case, but it is a good approximation). For the same reason, damaging central nodes […] can impair radically the flow of a network. Depending on the process one wants to study, other definitions of centrality can be introduced. For example, closeness centrality computes the distance of a node to all others, and reach centrality factors in the portion of all nodes that can be reached in one step, two steps, three steps, and so on.”

“Domino effects are not uncommon in foodwebs. Networks in general provide the backdrop for large-scale, sudden, and surprising dynamics. […] most of the real-world networks show a doubled-edged kind of robustness. They are able to function normally even when a large fraction of the network is damaged, but suddenly certain small failures, or targeted attacks, bring them down completely. […] networks are very different from engineered systems. In an airplane, damaging one element is enough to stop the whole machine. In order to make it more resilient, we have to use strategies such as duplicating certain pieces of the plane: this makes it almost 100 per cent safe. In contrast, networks, which are mostly not blueprinted, display a natural resilience to a broad range of errors, but when certain elements fail, they collapse. […] A random graph of the size of most real-world networks is destroyed after the removal of half of the nodes. On the other hand, when the same procedure is performed on a heterogeneous network (either a map of a real network or a scale-free model of a similar size), the giant connected component resists even after removing more than 80 per cent of the nodes, and the distance within it is practically the same as at the beginning. The scene is different when researchers simulate a targeted attack […] In this situation the collapse happens much faster […]. However, now the most vulnerable is the second: while in the homogeneous network it is necessary to remove about one-fifth of its more connected nodes to destroy it, in the heterogeneous one this happens after removing the first few hubs. Highly connected nodes seem to play a crucial role, in both errors and attacks. […] hubs are mainly responsible for the overall cohesion of the graph, and removing a few of them is enough to destroy it.”

“Studies of errors and attacks have shown that hubs keep different parts of a network connected. This implies that they also act as bridges for spreading diseases. Their numerous ties put them in contact with both infected and healthy individuals: so hubs become easily infected, and they infect other nodes easily. […] The vulnerability of heterogeneous networks to epidemics is bad news, but understanding it can provide good ideas for containing diseases. […] if we can immunize just a fraction, it is not a good idea to choose people at random. Most of the times, choosing at random implies selecting individuals with a relatively low number of connections. Even if they block the disease from spreading in their surroundings, hubs will always be there to put it back into circulation. A much better strategy would be to target hubs. Immunizing hubs is like deleting them from the network, and the studies on targeted attacks show that eliminating a small fraction of hubs fragments the network: thus, the disease will be confined to a few isolated components. […] in the epidemic spread of sexually transmitted diseases the timing of the links is crucial. Establishing an unprotected link with a person before they establish an unprotected link with another person who is infected is not the same as doing so afterwards.”

April 3, 2018 Posted by | Biology, Books, Ecology, Engineering, Epidemiology, Genetics, Mathematics, Statistics | Leave a comment

Promoting the unknown…

 

March 31, 2018 Posted by | Music | Leave a comment