The sound quality of this lecture is not completely optimal – there’s a recurring echo popping up now and then which I found slightly annoying – but this should not keep you from watching the lecture. It’s a quite good lecture, and very accessible – I don’t really think you even need to know anything about genetics to follow most of what he’s talking about here; as far as I can tell it’s a lecture intended for people who don’t really know much about population genetics. He introduces key concepts as they are needed and he does not go much into the technical details which might cause people trouble (this of course also makes the lecture somewhat superficial, but you can’t get everything). If you’re the sort of person who wants details not included in the lecture you’re probably already reading e.g. Razib Khan (who incidentally recently blogged/criticized a not too dissimilar paper from the one discussed in the lecture, dealing with South Asia)…
I must admit that I actually didn’t like this lecture very much, but I figured I might as well include it in this post anyway.
I found some questions included and some aspects of the coverage a bit ‘too basic’ for my taste, but other people interested in chess reading along here may like Anna’s approach better; like Krause’s lecture I think it’s an accessible lecture, despite the fact that it actually covers many lines in quite a bit of detail. It’s a long lecture but I don’t think you necessarily need to watch all of it in one go (…or at all?) – the analysis of the second game, the Kortschnoj-Gheorghiu game, starts around 45 minutes in so that might for example be a good place to include a break, if a break is required.
i. “to esteem every one is to esteem no one. […] the friend of all mankind is no friend of mine.” (Alceste, The Misanthrope, by Molière)
ii. “The art of not reading is a very important one. It consists in not taking an interest in whatever may be engaging the attention of the general public at any particular time. When some political or ecclesiastical pamphlet, or novel, or poem is making a great commotion, you should remember that he who writes for fools always finds a large public. A precondition for reading good books is not reading bad ones: for life is short.” (Schopenhauer)
iii. “people are never like what you remember them. You make them, as the years go by, more and more the way you wish them to be, and as you think you remember them. If you want to remember them as agreeable and gay and handsome, you make them far more so than they actually were.” (Poirot, in Agatha Christie’s Third Girl)
iv. “Youth is a failing only too easily outgrown.” (Agatha Christie, The Secret Adversary)
v. “There are faults which show heart and win hearts, while the virtue in which there is no love, repels.” (John Lancaster Spalding)
vi. “Solitude is unbearable for those who can not bear themselves.” (-ll-)
vii. “If we learn from those only, of whose lives and opinions we altogether approve, we shall have to turn from many of the highest and profoundest minds.” (-ll-)
viii. “The lover of education labors first of all to educate himself.” (-ll-)
ix. “The smaller the company, the larger the conversation.” (-ll-)
x. “What we acquire with joy, we possess with indifference.” (-ll-)
xi. “The innocence which is simply ignorance is not virtue.” (-ll-)
xii. “If our opinions rest upon solid ground, those who attack them do not make us angry, but themselves ridiculous.” (-ll-)
xiii. “(Respect)/(Required math) determines what academic field you should go into. Thus, economics is always a bad choice.” (Zach Weinersmith)
xiv. “there are important information effects of emotion. Emotions provide information about a situation that might be used in reasoning; it alters the way information provided in the reasoning statements is processed; and it influences what additional information may be activated during reasoning. […] emotional states are used strategically to orient reasoning strategies. For instance, sadness might indicate that there is a problem to be solved, and thus that a more careful, analytical mode of reasoning may be indicated. By contrast, positive moods signal that the individual is progressing towards their goals and that there is no urgent problem to solve; habitual, stereotypical ways of reasoning can thus be relied upon. […] anger seems to lead to more heuristic, less systematic processing […]. Similar effects have been observed for positive mood […] inducing positive or negative moods can be effective argumentative strategies to cover up weak arguments.” (Emotion and Reasoning, by Blanchette et al.).
xv. “People vary not only in the emotions they experience, but also in the degree to which they are aware of their own emotions, and emotional awareness influences the impact of emotions on beliefs. […] High emotional awareness has positive consequences when beliefs are adaptive. When the beliefs are maladaptive or destructive (the government is spying on me; I am worthless), high emotional awareness is linked to adverse consequences.” (-ll-)
xvi. “everyone knows they’re going to die, but no one really believes it.” (Spalding Gray)
xvii. “I guess this is why most maps of the solar system aren’t drawn to scale. It’s not hard to draw the planets. It’s the empty space that’s a problem. […] Most space charts leave out the most significant part – all the space.” (If the Moon Were Only 1 Pixel – A tediously accurate map of the solar system)
xviii. “There is no dress which embellishes the body more than science does the mind.” (Laurent Clerc)
xix. “It’s easier to hold to your principles 100% of the time than it is to hold to them 98% of the time.” (Clayton M. Christensen)
xx. “It would be a terrible mistake to go through life thinking that people are the sum total of what you see.” (Jonathan Tropper)
You can read my first post about the book, which lead to a brief comment exchange which may be of interest to people curious about diagnostics aspects, here. The book has a lot of stuff; in this post I’ll discuss the immune system, covered in chapter 5 of the book, as well as some ways that eating disorders may affect the skin (many of the remaining chapters of the book cover this topic). This will be my last post about the book.
In chapter 5 the authors start out by noting that adequate nutrition is an important factor in terms of maintaining immunocompetence and that malnutrition increases the risk of infection. Quite a few details are known about how specific aspects of nutritional deficiencies affect specific parts of the immune system. When both energy- and protein intake is insufficient (protein-energy malnutrition, PEM) this state of affairs is associated with atrophy of immune organs such as the thymus and spleen, as well as impairments in T cell populations (likely a natural consequence of thymus atrophy – the ‘T’ in ‘T cell’ stands for thymus…). Cytokine prodution (e.g. IL-1, IL-2, interferon-γ) is down-regulated in PEM, and the ability of T cells to respond appropriately to those cytokines is decreased. Impairments in macrophage phagocytotic function and neutrophils have been observed in malnourished individuals.
The authors note in the coverage that there now “seems to be consensus accepting that, overall, the manifestations of the immunocompromised status of ED patients are less frequent and severe than in PEM . In general, the immune function seems to be better preserved than would be expected, considering the highly defective nutritional status of the patients. […] [some of] the most frequent findings described are leukopenia [white blood cell deficiency] with relative lymphocytosis [increased proportion of lymphocytes in the blood], [and] thrombocytopenia [platelet deficiency] […] immunocompetence and particularly T cell subsets are useful tools to follow-up the nutritional status in patients with ED. This asseveration applies also to BN patients, since T cell subsets seem to reflect their subclinical malnutrition, which is not evident from their weight status. […] Vomiting as a purging strategy is associated with a more deleterious effect on T cells […] Complement-system proteins […] have been found decreased in AN [anorexia nervosa] and BN [bulimia nervosa] [6,79] [and] seem to depend also on white adipose tissue mass. […] These proteins might be useful in the follow-up of AN patients, since C3 and C4 falls seem to occur when treated patients resume their restricting habits increasing their risk of relapse .”
Despite eating disorders having significant effects on the immune system, infection risk in people with eating disorders seems surprisingly to not be elevated, at least not until an advanced stage of the disease has been reached. There are multiple explanations offered for this observation, but the answer as to why this is is not completely clear. One reason might be that people with eating disorders tend to maintain relatively high protein and vitamin intake in a manner dissimilar from the intake patterns associated with classic starvation, mediating the effects of energy deficiency. Two other reasons offered both relate to the fact that the immune system does not respond normally to pathogens, and so to the extent that symptoms relate to immune responses to infection people with eating disorders have fewer symptoms; this relates to both down-regulation of memory T-cells and suppressed capacity to mount the classic acute-phase response to infection; a reduced febrile response to bacterial infection has been observed in anorexics. In the context of muted responses to infection, the hormone leptin (‘the satiety hormone’) may also be implicated; “there is a function for leptin as an up-regulator factor of inflammatory immune responses. Moreover, leptin production is acutely increased during infection and inflammation […] an impairment in this acute increase in leptin production in AN patients might be related to the lack of infection symptoms in these patients .” Interestingly leptin also seems to be downregulated in BN.
Okay, let’s move on and talk a little bit about how eating disorders may affect the skin. The book has a lot of stuff about this so this will not be an exhaustive review of the material covered in the book – but I did think I ought to talk a little bit about this stuff. Skin signs are important in a diagnostic context: “As most patients with eating disorders tend to minimize or even deny their disorder, the skin changes are sometimes the only indication that the patient has an eating disorder.” Some of the skin signs described in the book relate quite directly to specific behaviours (e.g. vomiting in purging subtypes), whereas others are of a more generalized nature and are rather due to the fact that the body does not get enough energy/micronutrients/etc. to handle all the tasks it’s supposed to handle. Some skin signs are considered ‘guiding signs’ of eating disorders, in the sense that they’re signs often found in an eating disorder context but are not usually found in the differential diagnoses natural to consider in the given clinical context, so they can be used as guiding tools in a diagnostic context. Examples of guiding signs include “lanugo-like body hair [very fine, soft, and usually unpigmented, downy hair] due to starvation, Russell’s sign [calluses on the knuckles or back of the hand] and [tooth] enamel erosions due to self-induced vomiting, and self-induced dermatoses due to psychiatric comorbidity.”
Frequent skin signs in eating disorders include dry, scaly skin; orange discolouration of the skin due to excessive consumption of beta carotene (carrots); the aforementioned lanugo-like body hair; coldness of the extremities (feet, toes) and bluish/purplish colouring of the hands and feet, caused by slow circulation (acrocyanosis); hair loss; inflammation of the lips and nail changes. “With a BMI between 17.5 and 16, the skin is usually pale or yellowish and cold, but no specific signs are found.” They note in the book that “Russell sign, dental enamel erosion, and salivary gland enlargement [elsewhere in the coverage they also dub this phenomenon ‘“chipmunk” cheeks of the bulimic’] are pathognomonic of purging behavior”. Dry skin is reported in 70% of people with anorexia nervosa (-AN), and acne is reported in 47–59% of patients – these are very common symptoms/consequences of AN. The same is the case for lanugo; in one study of AN patients (n=62), 77% had lanugo. In one study, alopecia was present in 67% of bulimics (n=122) and 61% of anorexics (n=62).
Observing the hands may be important: “Strumia , observing the hand of the patients with anorexia nervosa (AN), noticed that many peculiar skin signs, such as xerosis, acrocyanosis, carotenoderma, evident blood vessels due to decreased subcutaneous tissue, cold hand, nail dystrophy [“Brittle nails affect approximately 30% of patients with anorexia nervosa and bulimia nervosa”], Russell’s sign and artefacta, were located on the hands. Strumia used the term “anorectic’s hand” and suggested that, by examining the hand of a young patient, one can reasonably suspect an eating disorder. Only Russell’s sign is pathognomonic of eating disorders, but at least three signs, excluding Russell’s sign, are required for the diagnosis of “anorectic’s hand”, for example, xerosis, carotenoderma and cold hand. A perspicacious dermatologist should pay attention to this important sign when it appears in young females that show signs of reduced self-esteem and distorted perception of body weight.”
It is noted in the book that classical deficiency syndromes such as scurvy are very rare in AN because “AN is not commonly associated with vitamin deficiencies” – rather it’s the case that many anorectics over-supplement on vitamin supplements, which can paradoxically induce or worsen some skin complaints, such as e.g. xerosis (dry skin).
“the progression of anorexic pathology is accompanied by changing patterns in dietary habits . These patterns include periods of low or no carbohydrate intake and an avoidance of dietary fats. They can also include patterns in which the primary foods consumed are fruits and vegetables. During this period, meat is often avoided. Changes in relative amounts of heavy to light isotopes [of nitrogen] in the hair indicate changes in the body’s metabolic state and dietary intake. […] By definition, individuals with anorexia or anorexia and bulimia are losing weight and do not get adequate nutrition. These individuals get their nitrogen largely from plants, and/or do not get sufficient nitrogen in their diet and are in nitrogen imbalance. By contrast, individuals diagnosed with only bulimia are maintaining their weight, and therefore get adequate nutrition and are likely not to be in nitrogen imbalance. […] Hatch et al. […] suggest that a distinction may be possible between anorexia and bulimia nervosa using 15N/14N and 13C/12C ratios in hair.”
“A reduced pain sensitivity has been found in eating disorder (ED) patients, but it is unclear what physiological and psychological factors are associated with this abnormality.”
This book is not exactly the first book I’ve read on these kinds of topics (see for example my previous coverage of related topics here, here, here, here, here, and here), but the book did have some new stuff and I decided in the end that it was worth blogging, despite the fact that I did not think the book was particularly great. The book is slightly different from previous books I’ve read on related topics because normative aspects are covered in much greater detail – as they put it in the preface:
“This volume addresses normative dimensions of methodological and theoretical approaches, international experiences concerning the normative framework and the process of priority setting as well as the legal basis behind priorities. It also examines specific criteria for prioritization and discusses economic evaluation. […] Prioritization is necessary and inevitable – not only for reasons of resource scarcity, which might become worse in the next few years. But especially in view of an optimization of the supply structures, prioritization is an essential issue that will contribute to the capability and stability of healthcare systems. Therefore, our volume may give useful impulses to face challenges of appropriate prioritization.”
I’m generally not particularly interested in normative questions, preferring instead to focus on the empirical side of things, but the book did have some data as well. In the post I’ll focus on topics I found interesting, and I have made no attempt here to make the coverage representative of the sort of topics actually covered in the book; this is (as usual) a somewhat biased account of the material covered.
The book observes early and often that there’s no way around prioritization in medicine; you can’t not prioritize, because “By giving priority to one group, you ration care to the second group.” Every time you spend a dollar on cancer treatment, well, that’s a dollar you can’t spend on heart disease. So the key question in this context is how best to prioritize, rather than whether you should do it. It is noted in the text that there is a wide consensus that approaching and handling health care allocation rules explicitly is preferable to implicit rationing, a point I believe was also made in Glied and Smith. A strong argument can be made that clear and well-defined decision-rules will lead to better outcomes than implicit allocation decisions made by doctors during their day-to-day workload. The risks of leaving allocation decisions to physicians involve overtaxing medical practitioners (they are implicitly required to repeatedly take decisions which may be emotionally very taxing), problematic and unfair distribution patters of care, and there’s also a risk that such practices may erode trust between patients and physicians.
A point related to the fact that any prioritization decision made within the medical sector, regardless of whether the decision is made implicitly or explicitly, will necessarily affect all patient populations by virtue of the fact that resources used for one purpose cannot be used for another purpose, is that the health care sector is not the only sector in the economy; when you spend money on medicine that’s also money you can’t be spending on housing or education: “The competition between health-related resources and other goods is generally left to a political process. The fact that a societal budget for meeting health needs is the result of such a political process means that in all societies, some method of resolving disagreements about priorities is needed.” Different countries have different approaches to how to resolve these disagreements (and in large countries in particular, lower-level regional differences may also be important in terms of realized care provision allocation decisions), and the book covers systems applied in multiple different countries, including England, Germany, Norway, Sweden, and the US state of Oregon.
Some observations and comments:
“A well-known unfairness objection against conventional cost-effectiveness analysis is the severity of diseases objection – the objection that the approach is blind as to whether the QALYs go to severely or to slightly ill patients. Another is the objection of disability discrimination – the objection that the approach is not blind between treating a life-threatening disease when it befalls a disabled patient and treating the same disease when it befalls a non-disabled patient. An ad hoc amendment for fairness problems like these is equity weighting. Equity weights are multiplication factors that are introduced in order to make some patient group’s QALYs count more than others.”
“There were an estimated 3 million people with diabetes in England in 2009; estimates suggest that the number of people with diabetes could rise to 4.6 million by 2030. There has also been a rapid rise in gastrointestinal diseases, particularly chronic liver disease where the under-65 mortality rate has increased 5-fold since 1970. Liver disease is strongly linked to the harmful use of alcohol and rising levels of obesity. […] the poorest members of the community are at most risk of neglecting their health. This group is more likely to eat, drink and smoke to excess and fail to take sufficient exercise.22 Accordingly, life expectancy in this community is shorter and the years spent of suffering from disability are much longer. […] Generic policies are effective in the sense that aggregate levels of health status improve and overall levels of morbidity and mortality fall. However, they are ineffective in reducing health inequalities; indeed, they may make them worse. The reason is that better-off groups respond more readily to public health campaigns. […] If policy-makers [on the other hand] disinvest from the majority to narrow the inequality gap with a minority resistant to change, this could reduce aggregate levels of health status in the community as a whole. [Health behaviours also incidentally tend to be quite resistant to change in general, and we really don’t know all that much about which sort of interventions work and/or how well they work – see also Thirlaway & Upton’s coverage] […] two out of three adults [in the UK] are overweight or obese; and inequalities in health remain widespread, with people in the poorest areas living on average 7 years fewer than those in the richest areas, and spending up to 17 more years living with poor health. […] the proportion of the total health budget invested in preventive medicine and health promotion […] is small. The UK spends about 3.6 % of its entire healthcare budget on public health projects of this nature (which is more than many other EU member states).”
Let’s talk a little bit about rationing. Rationing by delay (waiting lists) is a well-known method of limiting care, but it’s far from the only way to implicitly ration care in a manner which may be hidden from view; another way to limit care provision is to ration by dilution. This may happen when patients are seen on time (do recall that waiting lists are very common in the medical sector, for very natural reasons which I’ve discussed here on the blog before), but the quality of care that is provided to patients receiving care goes down. Rationing by dilution may sometimes be a result of attempts to limit rationing by delay; if you measure hospitals on whether or not they treat people within a given amount of time, the time dimension becomes very important in the treatment context and it may thus end up dominating other decision variables which should ideally take precedence over this variable in the specific clinical context. The book mentions as an example the Bristol Eye Hospital, where it is thought that 25 patients may have lost their sights because even though they were urgent cases which should have been high priority, they were not treated in time because there was a great institutional focus on not allowing waiting times of any patients on the waiting lists to cross the allowed maximum waiting time, meaning that much less urgent cases were treated instead of the urgent cases in order to make the numbers look good. A(n excessive?) focus on waiting lists may thus limit focus on patient needs, and similar problems pop up when other goals aside from patient needs are emphasized in an institutional context; hospital reorganisations undertaken in order to improve financial efficiency may also result in lower standards of care, and in the book multiple examples of this having happened in a British context are discussed. The chapter in question does not discuss this aspect, but it seems to me likely that rationing by dilution, or at least something quite similar to this, may also happen in the context of a rapid increase in capacity as a result of an attempt to address long waiting lists; if you for example decide to temporarily take on a lot of new and inexperienced nurses to lower the waiting list, these new nurses may not provide the same level of care as do the experienced nurses already present. A similar dynamic may probably be observed in a setting where the number of nurses does not change, but each patient is allocated less time with any given nurse than was previously the case.
“Public preferences have been shown not to align with QALY maximization (or health benefit maximization) across a variety of contexts […] and considerations affecting these preferences often extend well beyond strict utilitarian concerns […] age has been shown to be among the most frequently cited variables affecting the public’s prioritization decisions […] Most people are willing to use age as a criterion at least in some circumstances and at least in some ways. This is shown by empirical studies of public views on priority setting […] most studies suggest that a majority accepts that age can have some role in priority setting. […] Oliver [(2009)] found […] a wide range of context-dependent ‘decision rules’ emerged across the decision tasks that appeared to be dependent on the scenario presented. Respondents referenced reasons including maximizing QALYs,11 maximizing life-years or post-treatment quality of life,12 providing equal access to health care, maximizing health based on perceptions of adaptation, maximizing societal productivity (including familial roles, i.e. ‘productivity ageism’), minimizing suffering, minimizing costs, and distributing available resources equitably. As an illustration of its variability, he noted that 46 of the 50 respondents were inconsistent in their reasoning across the questions. Oliver commented that underlying values influence the respondents’ decisions, but if these values are context dependent, it becomes a challenge – if not impossible – to identify a preferred, overarching rule by which to distribute resources. […] Given the empirical observations that respondents do not seem to rely upon a consistent decision rule that is independent of the prioritization context, some have suggested that deliberative judgments be used to incorporate equity considerations […]. This means that decision makers may call upon a host of different ‘rules’ to set priorities depending on the context. When the patients are of similar ages, prioritization by severity may offer a morally justifiable solution, for example. In contrast, as the age discrepancy becomes greater between the two patients, there may be a point at which ‘the priority view’ (i.e. those who in the most dire conditions take precedence) no longer holds […] There is some evidence that indicates that public preferences do not support giving priority in instances where the intervention has a poor prognosis […] If older patients have poorer health outcomes as a result of certain interventions, [this] finding might imply that in these instances, they should receive lower priority or not be eligible for certain care. […] A substantial body of evidence indicates that the utilitarian approach of QALY maximization fails to adequately capture public preferences for a greater degree of equity into health-care distribution; however, how to go about incorporating these concerns remains unresolved.”
“roughly 35 % of the […] [UK] health expenditures were spent on the 13 % of our population over the age of 65. A similar statistic holds true for the European Union as well […] the elderly, on average, have many more health needs than the non-elderly. In the United States, 23 % of the elderly have five or more chronic health problems, some life-threatening, some quality-of-life diminishing (Thorpe et al. 2010). Despite this statistic, the majority of the elderly in any given year is quite healthy and makes minimal use of the health care system. Health needs tend to be concentrated. The sickest 5 % of the Medicare population consume 39 % of total Medicare expenditures, and the sickest 10 % consume 58 % of Medicare expenditures (Schoenman 2012). […] we are […] faced with the problem of where to draw the line with regard to a very large range of health deficiencies associated with advanced age. It used to be the case in the 1970s that neither dialysis nor kidney transplantation were offered as an option to patients in end-stage kidney failure who were beyond age 65 because it was believed they were not medically suitable. That is, both procedures were judged to be too burdensome for individuals who already had diminished health status. But some centers started dialyzing older patients with good results, and consequently, the fastest growing segment of the dialysis population today (2015) is over age 75. This phenomenon has now been generalized across many areas of surgery and medicine. […] What [many new] procedures have in common is that they are very expensive: $70,000 for coronary bypass surgery (though usually much more costly due to complication rates among the hyper-elderly); $200,000 for the LVAD [Left Ventricular Assist Device]; $100,000+ per month for prolonged mechanical ventilation. […] The average older recipient of an LVAD will gain one to two extra years of life […] there are now (2015) about 5.5 million Americans in various stages of heart failure and 550,000 new cases annually. Versions of the LVAD are still being improved, but the potential is that 200,000 of these devices could be implanted annually in the United States. That would add at least $40 billion per year to the cost of the Medicare program.”
“In the USA, around 40 % of premature mortality is attributed to behavioral patterns,2 and it is estimate[d] that around $1.3 trillion annually — around a third of the total health budget — is spent on preventable diseases.3 […] among the ten leading risk factors contributing to the burden of disease in high-income countries, seven can be directly attributed to unhealthy lifestyles. […] Private health insurance takes such factors into account when calculating premiums for health insurances (Olsen 2009). In contrast, publicly funded health-care systems are mainly based on the so-called solidarity principle, which generally excludes risk-based premiums. However, in some countries, several incentive schemes such as “fat taxes” […], bonuses, or reductions of premiums […] have recently been implemented in order to incorporate aspects of personal responsibility in public health-care systems. […] [An important point in this context is that] there are fundamental questions about whether […] better health leads to lower cost. Among other things, cost reductions are highly dependent on the period of time that one considers. What services are covered by a health system, and how its financing is managed, also matters. Regarding the relative lifetime cost of smokers, obese, and healthy people (never smokers, normal body mass index [BMI]) in the Netherlands, it has been suggested that the latter, and not the former two groups, are most costly — chiefly due to longer life and higher cost of care at the end of life.44 Other research suggests that incentivizing disease management programs rather than broader prevention programs is far more effective.45 Cost savings can therefore not be taken for granted but require consideration of the condition being incentivized, the organizational specifics of the health system, and, in particular, the time horizon over which possible savings are assessed. […] Policies seeking to promote personal responsibility for health can be structured in a very wide variety of ways, with a range of different consequences. In the best case, the stars are aligned and programs empower people’s health literacy and agency, reduce overall healthcare spending, alleviate resource allocation dilemmas, and lead to healthier and more productive workforces. But the devil is often in the detail: A focus on controlling or reducing cost can also lead to an inequitable distribution of benefits from incentive programs and penalize people for health risk factors that are beyond their control.”
In a surgical context prophylactic antibiotics are very often given to counter the risk of wound infection, especially in the gastrointestinal surgical context. The authors of the chapter don’t discuss the demerits of this approach at all, but I’ve read other people before who are critical of this way of doing things and before moving on to what the book has to say about related matters I thought I should remind you of some of the problems associated with the widespread prophylactic use of antibiotics in the surgical context – here’s part of what Gould and van der Meer had to say about this topic:
“Surgical prophylaxis is a common area of overuse [of antibiotics] as shown in many publications. Measured by total DDDs [defined daily doses], it can amount to around one third of a hospital’s total antibiotic use. This illustrates the potential for ecological damage although surgeons often ask whether 24 h or even single dose prophylaxis can really select for resistance. The simple answer is yes, but of course much of the problem is extension of prophylaxis beyond the perioperative period, often for several days in critical patients, perhaps until all lines and drains are removed. There is no evidence base in favour of such practices.” (link to further blog coverage of related topics here)
Omissions like these is incidentally one of several reasons why I did not give the Oxford handbook a higher rating than I did. With that out of the way let’s get back to the Oxford handbook coverage. They note in the surgery chapter that wound infection occurs in roughly one in five cases of elective GI surgery, and in up to 60 per cent of emergency surgery settings. Infections in surgical patients are not trivial events; they can lead to bleeding, wounds that reopen, and they can ultimately kill the patient. Another major risk associated with surgery in many different surgical contexts is the risk of deep vein thrombosis (-DVT). According to the book DVTs occur in 25-50% of surgical patients. That said, almost two-thirds of below-knee DVTs are asymptomatic and these rarely embolize to the lungs. Aside from surgery some other DVT risk factors worth knowing about include age (older patients are at higher risk), pregnancy, trauma, synthetic oestrogen (i.e., oral contraceptives), past DVT, cancer, obesity, and immobility.
As for DVTs in non-surgical contexts, I found it interesting that the book observes that “the evidence linking air travel to an increased risk of DVT is still largely circumstantial” – it also adds some additional data to contextualize the risk. For someone in the general population, the risk of DVT from a long-distance flight is estimated to be somewhere between one in 10.000 to one in 40.000, however for people in high-risk subgroups the incidence of DVT from flights lasting longer than 10 hours has been estimated at 4-6%. They argue in the book that travelers with multiple risk factors should consider compression stockings and/or a single prophylactic dose of low molecular-weight heparin for flights lasting longer than 6 hours; other ways to minimize risk include leg exercises, increased water intake and refraining from alcohol or caffeine during the flight. “There is no evidence to support the use of prophylactic aspirin.”
Even though I think a common impression is that surgeons always want to cut people open whereas internal medicine people will often think this is not necessary, ‘even surgeons’ are sometimes hesitant to cut you open. There are many reasons for this – the book covers a lot of surgical complications, but a perhaps particularly important long-term problem is this:
“Any surgical procedure that breaches the abdominal or pelvic cavities can predispose to the formation of adhesions [‘Adhesions are fibrous bands that form between tissues and organs, often as a result of injury during surgery. They may be thought of as internal scar tissue that connects tissues not normally connected’], which are found in up to 90% of those with previous abdominal surgery; this is why we do not rush to operate on small bowel obstruction: the operation predisposes to yet more adhesions. Handling of the serosal surface of the bowel causes inflammation, which over weeks to years can lead to the formation of fibrous bands that tether the bowel to itself or adjacent structures […] Their main sequelae are intestinal obstruction (the cause in ~60% of cases […]) and chronic abdominal or pelvic pain.”
Appendicitis is a lot more common than I’d thought; lifetime incidence is 6%, with risk peaking during the second decade of life; according to the book it is the most common surgical emergency. A diagnosis of appendicitis is often wrong; in up to one in five patients a healthy appendix is removed. Another very common surgical procedure is surgical repair of an inguinal hernia; more than 100.000 of these surgeries are performed in the UK each year.
Though the book has a separate chapter specifically dealing with the topic of oncology (and palliative care), the surgical chapter of course also covers various cancers and their treatments. You’ll encounter the usual encouraging remarks about diseases with a ‘gloomy prognosis and non-specific presentation’, ‘[m]ost patients […] present with locally advanced (inoperable) or metastatic disease’ (both quotes are on the topic of carcinoma of the stomach); ‘[s]urvival rates are poor with or without treatment’ (carcinoma of the oesophagus); ‘rare, have an overall poor prognosis and are difficult to diagnose’ (bile duct and gallbladder cancers), ‘~80% present with inoperable disease’ (bile duct cancer). It’s sort of hard to find it encouraging that colorectal carcinoma, another cancer covered in that chapter, in general tend to have lower mortality than these others (“Overall 5yr survival is ~50%”) when you also keep in mind that it’s one of the most common cancers (it is the second most common cause of cancer deaths in the United Kingdom, and the third most common cancer), and so kill a lot more people overall (16.000 deaths/year). Another thing to note is that the survival rate of patients with metastatic disease in this context is still really terrible; the treated 5-year survival rate for patients with distant metastases is reported to be 6.6%, compared to e.g. a 48% survival rate in treated cases with ‘only’ regional lymph node involvement. They observe in their coverage that “[l]aparoscopic surgery has revolutionized surgery for colon cancer. It is as safe as open surgery and there is no difference in overall survival or disease recurrence.”
There are many bodily changes which take place in people as they age, and some of the potentially problematic changes only occasionally cause symptoms despite their presence in a large number of people. One example is gastrointestinal diverticula. These are outpouchings of the gut wall which are present in many people but do not always cause problems. According to the authors, diverticulosis is a term used to indicate that diverticula are present, whereas diverticular disease implies they the diverticula are symptomatic; the term diverticulitis is used when there’s inflammation of the diverticula. 30 % of people at the age of 60 living in the West are estimated to have diverticulosis, but the majority are asymptomatic – they are a common incidental finding when people have colonoscopies. Although they often do not cause problems they can cause perforation and hemorrhage (e.g. large rectal bleeds); the former complication has a high mortality, ~40%. Lack of dietary fiber is thought to be implicated in the pathophysiological processes leading to diverticulosis. Gallstones is another example of a common condition many people have without knowing it; gallstone prevalence is estimated at 8% at the age of 40. Risk is increasing in age and is higher in obese people. 90% remain asymptomatic. Smoking is known to increase the risk that gallstones become symptomatic. Renal stones are also common, with lifetime incidence estimated to be ‘up to’ (?) 15%. However males are three times as likely to get renal stones as are females, so in males in particular these things are very common. In the case of small stones (<5mm in lower ureter) ~90-95 % pass spontaneously on their own. The simplest and easiest way to lower risk of kidney stones is to drink plenty of fluids (but keep in mind that tea increases oxalate levels and thus may contribute to stone formation…). They note that calculi may be asymptomatic but do not provide estimates of how often this is the case; I assume one reason is that it’s really very difficult to get a good estimate of how often people pass stones they did not know they had – you mostly learn about these things when they cause trouble. Making a brief jump back to the topic of cancers it should perhaps be noted that although cancer is not usually thought of as a really not very worrisome asymptomatic condition, some forms of cancer actually sometimes may be just that; autopsy studies have indicated that 80% of men above the age of 80 have some form of prostate cancer.
Stress incontinence is leakage from an incompetent sphincter for example when intra-abdominal pressure rises, which it may do when people laugh or cough. It is very common in pregnancy and following birth, and it “occurs to some degree in ~50% of post-menopausal women”.
Although I didn’t think much of the epidemiology chapter, I did want to include a few observations from the chapter in this post:
“In one study looking at recommendations of meta-analyses where there was a later ‘definitive’ big trial, it turned out that meta-analyses got it wrong 30% of the time”.
“During the time it takes you to read this page, your better-connected patients may have checked out the latest recommendations of Guatemalan Guidelines on Gynaecomastia, or the NICE’S Treatise on Toxoplasmosis. Patients have time and motivation, whereas we have little time and our motivation may be flickering. This can seem threatening to the doctor who sees himself as a dispenser of wisdom and precious remedies. It is less threatening if we consider ourselves to be in partnership with our patients. The evidence is that those who use the internet to question their therapy receive a better service.” (A lot of related topics were incidentally covered in the Cochrane handbook The Knowledgeable Patient: Communication and Participation in Health – see this post for data on and discussion of these things).
i. “The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data.” (John Tukey)
ii. “Far better an approximate answer to the right question, which is often vague, than an exact answer to the wrong question, which can always be made precise.” (-ll-)
iii. “They who can no longer unlearn have lost the power to learn.” (John Lancaster Spalding)
iv. “If there are but few who interest thee, why shouldst thou be disappointed if but few find thee interesting?” (-ll-)
v. “Since the mass of mankind are too ignorant or too indolent to think seriously, if majorities are right it is by accident.” (-ll-)
vi. “As they are the bravest who require no witnesses to their deeds of daring, so they are the best who do right without thinking whether or not it shall be known.” (-ll-)
vii. “Perfection is beyond our reach, but they who earnestly strive to become perfect, acquire excellences and virtues of which the multitude have no conception.” (-ll-)
viii. “We are made ridiculous less by our defects than by the affectation of qualities which are not ours.” (-ll-)
ix. “If thy words are wise, they will not seem so to the foolish: if they are deep the shallow will not appreciate them. Think not highly of thyself, then, when thou art praised by many.” (-ll-)
x. “Since all models are wrong the scientist cannot obtain a “correct” one by excessive elaboration. On the contrary following William of Occam he should seek an economical description of natural phenomena. Just as the ability to devise simple but evocative models is the signature of the great scientist so overelaboration and overparameterization is often the mark of mediocrity. ” (George E. P. Box)
xi. “Intense ultraviolet (UV) radiation from the young Sun acted on the atmosphere to form small amounts of very many gases. Most of these dissolved easily in water, and fell out in rain, making Earth’s surface water rich in carbon compounds. […] the most important chemical of all may have been cyanide (HCN). It would have formed easily in the upper atmosphere from solar radiation and meteorite impact, then dissolved in raindrops. Today it is broken down almost at once by oxygen, but early in Earth’s history it built up at low concentrations in lakes and oceans. Cyanide is a basic building block for more complex organic molecules such as amino acids and nucleic acid bases. Life probably evolved in chemical conditions that would kill us instantly!” (Richard Cowen, History of Life, p.8)
xii. “Dinosaurs dominated land communities for 100 million years, and it was only after dinosaurs disappeared that mammals became dominant. It’s difficult to avoid the suspicion that dinosaurs were in some way competitively superior to mammals and confined them to small body size and ecological insignificance. […] Dinosaurs dominated many guilds in the Cretaceous, including that of large browsers. […] in terms of their reconstructed behavior […] dinosaurs should be compared not with living reptiles, but with living mammals and birds. […] By the end of the Cretaceous there were mammals with varied sets of genes but muted variation in morphology. […] All Mesozoic mammals were small. Mammals with small bodies can play only a limited number of ecological roles, mainly insectivores and omnivores. But when dinosaurs disappeared at the end of the Cretaceous, some of the Paleocene mammals quickly evolved to take over many of their ecological roles” (ibid., pp. 145, 154, 222, 227-228)
xiii. “To consult the statistician after an experiment is finished is often merely to ask him to conduct a post mortem examination. He can perhaps say what the experiment died of.” (Ronald Fisher)
xiv. “Ideas are incestuous.” (Howard Raiffa)
xv. “Game theory […] deals only with the way in which ultrasmart, all knowing people should behave in competitive situations, and has little to say to Mr. X as he confronts the morass of his problem. ” (-ll-)
xvi. “One of the principal objects of theoretical research is to find the point of view from which the subject appears in the greatest simplicity.” (Josiah Williard Gibbs)
xvii. “Nothing is as dangerous as an ignorant friend; a wise enemy is to be preferred.” (Jean de La Fontaine)
xviii. “Humility is a virtue all preach, none practice; and yet everybody is content to hear.” (John Selden)
xix. “Few men make themselves masters of the things they write or speak.” (-ll-)
xx. “Wise men say nothing in dangerous times.” (-ll-)
Below are three new lectures from the Institute of Advanced Study. As far as I’ve gathered they’re all from an IAS symposium called ‘Lens of Computation on the Sciences’ – all three lecturers are computer scientists, but you don’t have to be a computer scientist to watch these lectures.
Should computer scientists and economists band together more and try to use the insights from one field to help solve problems in the other field? Roughgarden thinks so, and provides examples of how this might be done/has been done. Applications discussed in the lecture include traffic management and auction design. I’m not sure how much of this lecture is easy to follow for people who don’t know anything about either topic (i.e., computer science and economics), but I found it not too difficult to follow – it probably helped that I’ve actually done work on a few of the things he touches upon in the lecture, such as basic auction theory, the fixed point theorems and related proofs, basic queueing theory and basic discrete maths/graph theory. Either way there are certainly much more technical lectures than this one available at the IAS channel.
I don’t have Facebook and I’m not planning on ever getting a FB account, so I’m not really sure I care about the things this guy is trying to do, but the lecturer does touch upon some interesting topics in network theory. Not a great lecture in my opinion and occasionally I think the lecturer ‘drifts’ a bit, talking without saying very much, but it’s also not a terrible lecture. A few times I was really annoyed that you can’t see where he’s pointing that damn laser pointer, but this issue should not stop you from watching the video, especially not if you have an interest in analytical aspects of how to approach and make sense of ‘Big Data’.
I’ve noticed that Scott Alexander has said some nice things about Scott Aaronson a few times, but until now I’ve never actually read any of the latter guy’s stuff or watched any lectures by him. I agree with Scott (Alexander) that Scott (Aaronson) is definitely a smart guy. This is an interesting lecture; I won’t pretend I understood all of it, but it has some thought-provoking ideas and important points in the context of quantum computing and it’s actually a quite entertaining lecture; I was close to laughing a couple of times.
i. “The educated don’t get that way by memorizing facts; they get that way by respecting them.” (Tom Heehler)
ii. “The things you think about determine the quality of your mind. Your soul takes on the color of your thoughts.” (Marcus Aurelius)
iii. “There is no man so fortunate that there shall not be by him when he is dying some who are pleased with what is going to happen.” (-ll-)
iv. “Most of what we say and do is not necessary, and its omission would save both time and trouble. At every step, therefore, a man should ask himself, ‘Is this one of the things that are superfluous?’.” (Marcus Aurelius, as quoted in Bill Gillham’s book Case Study Research Methods, page 97)).
v. “statistics only lie to those who don’t understand them.” (Bill Gillham, Case Study Research Methods, page 80).
vi. “Few know the joys that spring from a disinterested curiosity. It is like a cheerful spirit that leads us through worlds filled with what is true and fair, which we admire and love because it is true and fair.” (John Lancaster Spalding)
vii. “The teacher does best, not when he explains, but when he impels his pupils to seek themselves the explanation.” (-ll-)
viii. “As our power over others increases, we become less free; for to retain it, we must make ourselves its servants.” (-ll-)
ix. “They who truly know have had to unlearn hardly less than they have had to learn.” (-ll-)
x. “They who no longer believe in principles still proclaim them, to conceal, both from themselves and others, the selfishness of the motives by which they are dominated.” (-ll-)
xi. “When we have not the strength or the courage to grasp a new truth, we persuade ourselves that it is not a truth at all.” (-ll-)
xii. “We neglect the opportunities which are always present, and imagine that if those that are rare were offered, we should put them to good use. Thus we waste life waiting for what if it came we should be unprepared for.” (-ll-)
xiii. “The inclination to seek the truth is safer than the presumption which regards unknown things as known.” (Augustine of Hippo)
xiv. “It is no advantage to be near the light if the eyes are closed.” (-ll-)
xv. “The true test of intelligence is not how much we know how to do, but how we behave when we don’t know what to do.” (John Holt)
xvi. “The most important thing any teacher has to learn […] can be expressed in seven words: Learning is not the product of teaching. Learning is the product of the activity of learners.” (-ll-)
xvii. “It is not just power, but impotence, that corrupts people. It gives them the mind and soul of slaves. It makes them indifferent, lazy, cynical, irresponsible, and, above all, stupid.” (-ll-)
xviii. “No man ever became extremely wicked all at once.” (Juvenal)
xix. “those who live in the West or in middle-class urban enclaves in the Non-west […] have to make a determined effort to grasp the grimness of past reality for most of humankind. In non-privileged, non-modern societies, most people in times past were malnourished, inadequately clothed against the elements, unwashed and filthy, living with insect parasites in overcrowded hovels. […] In these circumstances, “ill-health” […] very often simply meant that one was too incapacitated to carry on working in the fields or in the shop. It did not mean that one woke up feeling slightly off-color […] in the world we have lost, feeling somewhat off-color (or worse) was the standard condition.” (Disease and Medicine in World History, by Sheldon Watts, pp. 9-10).
xx. “In pre-modern China […] the task of establishing standard medical-related interpretations and texts was undertaken largely by philosophers and other scholars intent on building up grand systems which explained everything in the universe. Given that purpose, they did not attempt to build systems based on knowledge of the organs in an actual human body. […] At least until the mid-eighteenth century CE, well-known medico-philosophers [in China] wove the concept of “demon” as disease-cause-to-be-cleansed-away-by-exorcism into textual interpretations of what actually caused disease and what should be done about it.” (ibid., pp. 70, 72).
“Dermatologists have an important role in the early diagnosis of eating disorders since skin signs are, at times, the only easily detectable symptoms of hidden anorexia and bulimia nervosa. Forty cutaneous signs have been recognized”
The full title of the book is Eating Disorders and the Skin, but there’s a lot of stuff about eating disorders in general in this book as well, and I figured I’d mostly focus on the ‘general stuff’ in this post. Here’s my goodreads review of the book, which I gave 3 stars.
Here are the DSM-IV-TR diagnostic criteria for anorexia nervosa:
“1. Refusal to maintain body weight at or above a minimally normal weight for age and height (e.g., weight loss leading to maintenance of body weight less than 85% of that expected, or failure to make expected weight gain during period of growth, leading to body weight less than 85% of that expected).
2. Intense fear of gaining weight or becoming fat even though underweight.
3. Disturbance in the way in which one’s body weight or shape is experienced, undue influence of body weight or shape on self-evaluation, or denial of the seriousness of the current low body weight.
4.4. In postmenarcheal females, amenorrhea, i.e., the absence of at least three consecutive menstrual cycles.”
Interestingly, aside from anorexia [-AN] and bulimia [-BN] (diagnostic criteria here), there’s also a big category called ED-NOS – Eating Disorder Not Otherwise Specified. That’s for cases that don’t really fit into the standard criteria for specific eating disorders; they note than an example of this type could be a female fitting all diagnostic criteria for AN except that she has regular menses. It is perhaps worth mentioning here that surprisingly enough (…to me), menstrual irregularities are not limited to cases of AN, thus: “In almost 50% of bulimic patients, menstrual irregularities, such as oligomenorrhea or amenorrhea, take place”. They note in the book that there’s been some concern about the validity of the ED-NOS category, which makes up almost 60% of patients with an eating disorder. Eating disorders are much more common in females than in males (“Males are generally reported to account for 5–10% of anorectics and 10–15% of bulimics identified in the general population”), and particular subgroups mentioned to be at high risk are athletes, models and dancers. It’s noted in the book that most epidemiological studies are conducted in high-risk settings, whereas epidemiological studies assessing risk in the general population are somewhat rarer. One problem complicating matters a little in terms of estimating risk is that an eating disorder cannot be diagnosed through a self-report questionnaire; you need a structured or semi-structured interview to make a diagnosis, which makes things more expensive. As in other contexts one way to get around this issue, at least to some extent, is to employ multi-step screening protocols – in this case a two-step procedure in which individuals at high risk are identified at the first step through inexpensive means, and these individuals are then later assessed more carefully in the second step, employing more accurate (and expensive) methods.
They note that in Western countries, point prevalence of AN in female adolescent (the highest risk sub-group) is estimated at 0.2-1% of the population, whereas the prevalence studies on bulimia nervosa indicates that this eating disorder is somewhat more common, with the majority of studies finding prevalences of 1.5-5%; do recall again that most studies as already mentioned look at high-risk subgroups, so total population prevalence is likely to be lower than this. They observe in the book that general-practice studies find that the incidence of anorexia nervosa is less than one in ten-thousand per year (8 per 100,000 per year); so full-blown AN certainly is likely quite rare in low-risk populations.
On lifetime risk, the book notes that:
“Most of the epidemiological studies on ED [eating disorders] have evaluated the prevalence of full syndromes of both AN [anorexia nervosa] and BN [bulimia nervosa]. The few studies that have evaluated partial or subclinical manifestations of EDs in young females, however, found lifetime prevalence rates of 5–12% for atypical AN and 1–4.8% for atypical BN and up to 14.6% in adolescent samples”.
A review of epidemiological studies concluded that there’s no evidence of either a secular increase in AN or BN over time; to the extent that the number of people with diagnosed BN has increased over time, changes in diagnostic and referral practices likely account for this. On a related topic it is noted in the book that “It is a common idea among clinicians that early-onset cases of anorexia nervosa (AN) are increasing, but few data in the literature are available to demonstrate this trend.”
AN most commonly present among females at the age of 15-19, whereas BN presents a little later, most commonly at the age of 20-24. But eating disorders are not limited to teenagers and young adults: “Even if anorexia nervosa and bulimia nervosa occur characteristically in females during adolescence and young adulthood, there have been case reports of illness beginning after the age of 25 and even after the menopause, and some authors suggest that the rates of eating disorders in older patients may be increasing . Clinical impression suggests that the late-onset cases present with more depressive features than the adolescent counterpart. […] dieting is considered one of the most salient precipitating factors.”
Self-report metrics can only help you so much when you’re trying to assess risk; a major problem in this context is that denial of illness is a very common feature in these patient populations (so you certainly can’t just ask people if their relationship with food/exercise etc. might be unhealthy…): “typically, [the] course [of an eating disorder] is characterized by a high fluidity between the diagnostic classes; furthermore, the patient often denies even to himself the psychiatric nature of the disease” (recall also that “denial of the seriousness of the current low body weight” is included in the diagnostic criteria). The book covers a lot of symptoms which relate to low body weight – like cold intolerance, bradycardia (slow heart rate), acrocyanosis (bluish discoloration of the hands and feet, caused by slow circulation), systemic hypotension (low blood pressure), lots of skin signs (I haven’t decided yet how much detail I’ll go into, so let’s leave it at that now) – or e.g. to purging behaviours (throat and tooth pain due to vomiting and enamel erosion), but it would go much too far to discuss all these in detail here. One to me interesting aspect of the coverage was that whereas BMI is a useful sign, it’s not itself a diagnostic criterion; the authors note that a BMI below 18.5 is considered pathological, but when listing main signs of anorexia nervosa the most important diagnostic sign (or at least the first one listed) is a BMI below 17.5; I assume part of the discussion surrounding the validity of the ED-NOS category probably relate to individuals who’re in this ‘border area’; they likely have some symptoms due to low body mass (like e.g. cold intolerance), but they don’t have full-blown AN (there are a lot of things that can go wrong when you have low body mass – there are a lot of symptoms described in this book!). It’s also important to note that very different symptom patterns can be present at similar levels of BMI, as the severity of symptoms also relate to how fast body mass decreases – the body is actually capable of adjusting quite well to lower energy intake states (in the short run at least), and so “if weight loss is gradual, it is possible to maintain, even for a long time, an apparent metabolic equilibrium.”
Anorexics have high mortality rates: “From a meta-analysis of 119 studies involving 5,590 patients, Steinhausen reported a crude mortality rate of 5% which exceeded 9% in a followup of 10 years.” Remember when thinking about those estimates that most of the people in these studies were likely young women – these numbers are high, and the authors note that anorexia nervosa “represents the major cause of death of young women in the age between 12 and 25 years.”
Most deaths are due to ventricular arrhythmia; the book goes into some detail about how anorexia affects the cardiovascular system, but I won’t discuss this in detail. An important observation is that: “Cardiac findings tend to disappear with weight recovery.” I assume this comment relates mostly to findings like QTc prolongation, QTc dispersion, and mitral valve prolapse, all of which are found in anorexics, whereas I’d be surprised if cardiac abnormalities related to direct damage to the heart muscle resolve themselves after weight gain, but the book does not go into details on this topic, except in the sense that it is noted that heart failure is uncommon in anorexics. Among those who survive their illness, osteoporosis is a major irreversible long-term problem. People with higher body mass tend to have a higher bone mineral density and thus a lower risk of osteoporosis (unless they get type 2 diabetes, in which case the situation is, well, complicated), so perhaps it’s not really surprising that women with AN and very low body mass index tend to develop osteoporosis. They certainly do:
“Osteopenia and osteoporosis represent one of the most relevant and potentially not reversible complications of eating disorders. This complication is particularly severe when eating disorders have an early onset […] Bone loss is an early effect of the disease, already present after 6–12 months […] In untreated patients, bone loss ranges from 4% up to 10% per year […]. In case of recovery, the progressive loss of BMD [bone mineral density] stops, but in most cases, a normal bone mass is not restored .”
It’s noted that bone loss is due to both hormonal and metabolic factors; estrogen plays a role, and “BMD loss in AN is more rapid and severe than in other hypoestrogenic conditions”. Despite this observation weight gain is considered the primary treatment modality of osteoporosis in this context (i.e., not estrogen therapy), and research using estrogen therapy to try to boost bone mineral density in anorexics who did not also gain weight has not been successful.
A to me interesting aspect of the coverage which I could not help but discuss here is how eating disorders relate to diabetes; the book has a few remarks on this topic:
“The concurrence of an eating disorder with insulin-dependent diabetes has been outlined by several researchers: especially bulimia nervosa and disorder not otherwise specified (EDNOS) are reported to be significantly higher in females with type 1 diabetes […] In case of comorbidity, ED onset followed the diagnosis of IDDM in 70% of the patients . Specific aspects of diabetes and its management could, in fact, potentially increase a particular susceptibility to the development of an eating disorder: weight gain, associated with initiation of insulin treatment and dietary restraint, might, in fact, trigger body dissatisfaction and the drive for thinness with consequent weight control behaviors ranging from healthy to very unhealthy behaviors […] insulin omission [is] a common weight loss behavior in girls with IDDM and eating disorder […] APA Guidelines 2006 suggest that insulin omission should be considered a specific type of purging behavior in the next DSM revision”.
I don’t know if this suggested change has been implemented at this point, but it would make a lot of sense. To people who don’t know what this ‘insulin omission’ they talk about is all about, the short version is that if you’re a type 1 diabetic in need of regular insulin injections, if you don’t take enough insulin you lose weight and you can eat pretty much whatever you like without gaining weight; which is of course an unfortunate though likely very attractive option for young women to have. The downside of engaging in systematic insulin omission behaviour of that kind is that you’ll likely go blind from your diabetes and/or die of kidney failure or DKA if you do that for an extended period of time.
Below I have posted a list of books I’ve read to completion in 2015, as well as links to blog posts covering the books and reviews of the books which I’ve written on goodreads. At the bottom of the post I have also added the books I did not finish this year, as well as some related links and comments. If you want ‘the big picture’, goodreads has made a very nice ‘my year in books‘ collection with covers and ratings of the books, as well as a few summary statistics. The goodreads overview also includes books I did not read in full, which is why the number of books included in that overview (160) is higher than the number of books on the list below.
Before I move on to the list, I want to talk a little bit about what’s on it and add some data – people who just want to peruse the list of books and links are welcome to skip the next few paragraphs, though I do believe they add some relevant context which might be of interest.
The major change (which isn’t really all that ‘major’, to be honest…) to this year’s list, compared to the 2014 book list, is the inclusion of an additional category, the ‘t/m’ (travel/miscellaneous) category. The other two categories on the list are fiction (-f) and non-fiction (-nf). According to the goodreads overview to which I linked above, I read 44,892 pages in 2015 (~123 pages/day), and the average page count of the books I read was 284. During the year I finished 153 books, which translates into roughly 3 books per week, with one of those three books (51 books altogether) being what I might term ‘serious non-fiction’. There are 10 books in the travel/miscellaneous category and most of these are categorized as non-fiction on sites like goodreads, so the number of non-fiction books depends a bit on how you categorize these things – if I had not added the new travel/miscellaneous category the number of non-fiction books might have been close to 60, but I did not like that categorization model because it seemed to me to lump together books which I did not really think ‘belonged together’. As it is, roughly 40% of all non-fiction books I read (20 books) were published by Springer or Oxford University Press, with most of the remainder being publications from other academic publishers. It should perhaps be noted in this context that although most of the books in the miscellaneous category are light reading, the category does also include Scott’s Last Expedition, an ~850 pages long book on which I spent roughly 25 hours (that one I for a while strongly considered moving to the non-fiction category).
Since I use categories quite systematically when covering non-fiction books on the blog, I decided to use these categories to get a handle on which topics I’ve read about during the year. It turns out that I have posted 20 posts about books dealing with both the topics of medicine and psychology. I posted 12 posts about books dealing with the topic of diabetes, 8 posts about books dealing with the topic of biology, and 7 about books dealing with the topic of statistics. Minor categories include economics (6 posts each), mathematics and zoology (5 posts each), as well as cancer, evolution, alcohol, and anthropology (4 posts each). In terms of books I’ve covered, I have covered 11 books about psychology, 10 books about medicine, and 9 books about diabetes. Other key topics include mathematics and statistics (5 books each), and economics and biology (4 books each).
Although I did cover the majority of the non-fiction books I read during the year on the blog, there is a substantial proportion of books which I either only reviewed on goodreads or did not review at all; the counts above do not include the topics covered in these 21 books, so although the count is an accurate representation of the sort of posts you may find on the blog, they may not be an accurate representation of the sort of books I read during the year; some books are easier to blog than others. I tried to informally estimate the magnitude of this implicit selection bias by trying to figure out which categories I might have used had I found the time to blog the non-fiction books I did not get around to blogging this year; you can probably quibble over the details in one or two cases, but in most cases it seemed reasonably easy for me to figure out which main categories I would have used in connection with a specific book – it doesn’t take a lot of work to realize that a book named ‘Prioritization in Medicine’ would probably be categorized as ‘medicine’, or that a history book would go into the ‘history’ bin. According to my count, among books not included in the count above there were 6 books which I think I would have blogged under the ‘medicine’ category, 6 I would have blogged under the ‘psychology’ category, 5 books about statistics and 4 books I would have categorized under ‘history’. The remaining categories which I considered it likely I would have used were biology and physics (2 each), and philosophy and linguistics (1 each); the implicit posting bias doesn’t appear to be too bad, though it does look as if books on statistics in particular seem, not surprisingly (to me), to be less likely than other books to ‘get a blog post’, rather than a goodreads review (there were few non-fiction books which I did not either blog or review on goodreads). This makes sense because stats posts tend to take a lot of time to write, so I don’t find it surprising that I only ended up blogging half of the 10 statistics books I finished this year. A related reason is probably that a few of those books covered topics I have already covered here on the blog; I have for example already read multiple epidemiology textbooks at this point, and if the book doesn’t add much new stuff I see no reason to blog it.
It should be noted that the above numbers are ‘subject to change’ because there are still some books I read in 2015 which I would like to blog later on, and so what’ll happen in 2016 is that I’ll add more links over time to this post until it covers all the posts and books I want to cover, but I’ll leave the outline above the way it was at the time I wrote this post as it would be a lot of work to modify all the relevant numbers above every time I add a new blog post to this link collection.
I don’t blog fiction these days, but given how much fiction I’m reading at the moment I probably should add a few comments on that topic as well. 2015 was the year I discovered P. G. Wodehouse; a clear majority of the fiction books I read this year (61 books) were written by Wodehouse. I also read 13 books by Agatha Christie; the remainder of my fiction reading was spread out over quite a few authors.
Before moving on to the list I should of course mention that recommendations are always welcome and that I’m always curious to know which kinds of books other people are reading…
The list of books I finished:
3. The Eye of Zoltar (f). Jasper Fforde.
4. Statistical Models for Proportions and Probabilities (nf. Springer). Blog coverage here.
7. Chamberlain’s Symptoms and Signs in Clinical Medicine: An Introduction to Medical Diagnosis (4, nf. CRC Press). Blog coverage here, here, here, and here.
8. Diabetes: The Biography (5, nf. Oxford University Press). My goodreads review is worth reposting here: “This book is awesome. This is simply a wonderful account of the history of diabetes. Highly recommended.” Blog coverage here.
10. Model Selection and Multi-Model Inference: A Practical Information-Theoretic Approach (5, nf. Springer). Goodreads review here. Blog coverage here and here.
11. Recountings: Conversations with MIT Mathematicians (4, nf. AK Peters). Blog coverage here.
12. Whose Body? (2, f). Dorothy Sayers.
13. Clouds of Witness (3, f). Dorothy Sayers.
14. Introduction to Systems Analysis: Mathematically Modeling Natural Systems (3, nf. Springer). Note that goodreads has listed this book under the wrong title, which is the reason why the title in this post deviates from the title on goodreads. Goodreads review here. Blog coverage here.
15. Unnatural Death (2, f). Dorothy Sayers.
16. Mammoths, Sabertooths, and Hominids: 65 Million Years of Mammalian Evolution in Europe (4, nf. Columbia University Press). Blog coverage here, here, and here.
17. Belief-Based Stability in Coalition Formation with Uncertainty: An Intelligent Agents’ Perspective (2, nf. Springer). Blog coverage here.
18. Lord Peter Views the Body (2, f). Dorothy Sayers.
20. Leave It to Psmith (5, f). P. G. Wodehouse.
21. Summer Lightning (5, f). P. G. Wodehouse.
22. The Psychology of Lifestyle: Promoting Healthy Behaviour (2, nf. Routhledge). Blog coverage here, here, and here.
23. Blandings Castle and Elsewhere (3, f). P. G. Wodehouse.
24. Thank You, Jeeves (5, f). P. G. Wodehouse.
25. Right Ho, Jeeves (5, f). P. G. Wodehouse.
26. The Code of the Woosters (4, f). P. G. Wodehouse.
27. Uncle Fred in the Springtime (5, f). P. G. Wodehouse.
28. The Inimitable Jeeves (3, f). P. G. Wodehouse.
29. A Damsel in Distress (4, f). P. G. Wodehouse.
30. Full Moon (5, f). P. G. Wodehouse.
31. Cocktail Time (5, f). P. G. Wodehouse.
33. Picadilly Jim (5, f). P. G. Wodehouse.
35. A Systematic Review of Key Issues in Public Health (1, nf. Springer). Goodreads review here. Blog coverage here and here.
36. Meet Mr. Mulliner (2, f). P. G. Wodehouse.
37. The Hungry Mind: The Origins of Curiosity in Childhood (2, nf. Harvard University Press). Short goodreads review here. Blog coverage here and here.
38. Care Giving for Alzheimer’s Disease – A Compassionate Guide for Clinicians and Loved Ones (1, nf. Springer). Goodreads review here.
39. Money for Nothing (3, f). P. G. Wodehouse.
40. The Small Bachelor (3, f). P. G. Wodehouse.
41. Neither here Nor there: Travels in Europe (5, t/m. Black Swan). Bill Bryson. This book is very funny!
42. The Lost Continent: Travels in Small-town America (2, t/m. Black Swan). Bill Bryson.
43. Life on a Young Planet: The First Three Billion Years of Evolution on Earth (3, nf. Princeton University Press).
44. Notes from a Small Island (2, t/m. Black Swan). Bill Bryson.
45. Laughing Gas (4, f). P. G. Wodehouse.
46. A Pelican at Blandings (3, f). P. G. Wodehouse.
48. Providing Practical Support For People With Autism Spectrum Disorders: Supported Living In The Community (2, nf. Jessica Kingsley Publishers). Short goodreads review here. Blog coverage here.
53. Down Under (4, t/m. Black Swan). Bill Bryson.
55. The Complete Yes Minister (5, f). Jonathan Lynn & Anthony Jay.
57. Pigs Have Wings (4, f). P. G. Wodehouse.
60. Summer Moonshine (3, f). P. G. Wodehouse.
61. Practical Approaches to Causal Relationship Exploration (nf. Springer). Goodreads review here.
62. Quick service (3, f). P. G. Wodehouse.
63. Spring Fever (4, f). P. G. Wodehouse.
64. Chronic Depression: Interpersonal Sources, Therapeutic Solutions (2, nf. American Psychological Association). Short goodreads review here. Blog coverage here and here.
66. Money in the Bank (4, f). P. G. Wodehouse.
67. A Walk in the Woods: Rediscovering America on the Appalachian Trail (3, t/m. Anchor Books). Bill Bryson.
68. The Prince and Betty (3, f). P. G. Wodehouse.
71. Made in America: An Informal History of the English Language in the United States (3, nf. Avon Books). Goodreads review here.
74. The Gem Collector (3, f). P. G. Wodehouse.
81. Psychological Aspects of Cyberspace: Theory, Research, Applications (2, nf. Cambridge University Press). Goodreads review here.
82. Partner Violence: A New Paradigm for Understanding Conflict Escalation (1, nf. Springer). Goodreads review here. Blog coverage here and here.
83. The Importance of Being Earnest (3, f). Oscar Wilde.
85. Applied Methods of Cost-Effectiveness Analysis in Healthcare (Handbooks in Health Economic Evaluation) (5, nf. Oxford University Press). Blog coverage here, here, and here.
86. Joy in the Morning (5, f). P. G. Wodehouse.
88. The Mating Season (4, f). P. G. Wodehouse.
90. Jeeves in the Offing (4, f). P. G. Wodehouse.
91. Stiff Upper Lip, Jeeves (5, f). P. G. Wodehouse.
92. Waves (The MIT Press Essential Knowledge Series) (3, nf. MIT Press).
93. Jeeves and the Feudal Spirit (4, f). P. G. Wodehouse.
94. Much Obliged, Jeeves (4, f). P. G. Wodehouse.
96. Loneliness: Human Nature and the Need for Social Connection (2, nf. W. W. Norton & Company). Blog coverage here, here, and here.
100. On the Origin of Species by Means of Natural Selection, or the Preservation of Favoured Races in the Struggle for Life (nf.). Charles Darwin. Blog coverage here.
101. Galahad at Blandings (5, f). P. G. Wodehouse.
103. Epidemiology Matters: A New Introduction to Methodological Foundations (2, nf. Oxford University Press). Goodreads review here.
106. Band of Brothers: E Company, 506th Regiment, 101st Airborne from Normandy to Hitler’s Eagle’s Nest (2, nf. Pocket Books/Stephen Ambrose). Goodreads review here.
108. Simply Rational: Decision Making in the Real World (4, nf. Oxford University Press). Goodreads review here. This SSC comment includes a few quotes from the book.
109. Mathematically Speaking: A Dictionary of Quotations (2, nf. Taylor & Francis Group). Goodreads review here. Blog coverage here.
110. The Luck of the Bodkins (4, f). P. G. Wodehouse.
113. The Nature of Statistical Evidence (Lecture Notes in Statistics) (3, nf. Springer). Goodreads review here. Blog coverage here.
114. Understanding Other-Oriented Hope: An Integral Concept Within Hope Studies (1, nf. Springer). Goodreads review here. Blog coverage here.
116. Peripheral Neuropathy & Neuropathic Pain: Into the light (5, nf. Tfm Pub Ltd). Blog coverage here and here.
117. The Adventures of Sally (4, f). P. G. Wodehouse.
121. The Man Upstairs and Other Stories (3, f). P. G. Wodehouse.
123. Scott’s Last Expedition (Classics of World Literature) (4, t/m. Wordsworth Editions). Long (848 pages). Goodreads review here.
124. Hot Water (4, f). P. G. Wodehouse.
127. The Little Nugget (3, f). P. G. Wodehouse.
128. Ring For Jeeves (4, f). P. G. Wodehouse.
130. Diabetic Bone Disease: Basic and Translational Research and Clinical Applications (5, nf. Springer). Blog coverage here.
131. Very Good, Jeeves! (4, f). P. G. Wodehouse.
133. Dead Man’s Folly (4, f). Agatha Christie.
137. Uncle Dynamite (4, f). P. G. Wodehouse.
139. Prioritization in Medicine: An International Dialogue (2, nf. Springer). Blog coverage here.
142. Physically Speaking: A Dictionary of Quotations on Physics and Astronomy (2, nf. Taylor & Francis Group). Goodreads review here. Blog coverage here.
143. Sparkling Cyanide (4, f). Agatha Christie.
146. Why Didn’t They Ask Evans? (2, f). Agatha Christie.
149. The Seven Dials Mystery (3, f). Agatha Christie.
152. History of Life (5, nf. Wiley-Blackwell). “In short, this is a wonderful book about the history of life on Earth, and I highly recommend it” – a quote from my goodreads review of the book. I added this book to my list of favorite books on goodreads.
153. Mrs. McGinty’s Dead (4, f). Agatha Christie.
Below I have added a short list of books I did not finish this year:
The Geometry of Special Relativity (nf. AK Peters).
Seas and Waterways of the World, Volume 1 & 2: An Encyclopedia of History, Uses, and Issues (1, nf. ABC-CLIO). Goodreads review here.
Fundamentals of Geophysical Fluid Dynamics (nf. Cambridge University Press). Not a bad book, but back when I was reading it I ended up concluding that it was simply too demanding to be worth finishing – it’s very math-heavy.
Learn from the Legends: Chess Champions at Their Best (nf. Quality Chess). I didn’t particularly like Marin’s writing style as I think the book has way too much fluff and too many irrelevant details/anecdotes, and the book was not engaging enough to motivate me to analyze the included games and positions in the amount of depth required to get much out of a book like this one. A somewhat disappointing read, which was why I did not finish it.
The Science of Reading: A Handbook (nf. Wiley-Blackwell). I found this book much too boring to be worth my time, and after approximately 100 pages I’d had enough. I might decide later on to have another go at it, but I don’t think it’s very likely that I’ll read this book from cover to cover the way I intended to when I started out reading it. The Eysenck and Keane text cover some of the same topics covered in the first part of this book, and I liked their coverage better although they go into much less detail (one to me not implausible inference being that I simply don’t care enough about the topics covered in this book to read about them in the amount of depth/detail they’re covered in this textbook).
Transdisciplinary Public Health: Research, Education, and Practice (1, nf. Jossey-Bass Education). Goodreads review here.
A Handbook of Statistical Analyses using SAS (CRC Press).
100 Endgames You Must Know (New in Chess).
Explaining Behavior: Reasons in a World of Causes (Bradford Book).
Here’s my goodreads review of the book. As mentioned in the review, the book was overall a slightly disappointing read – but there were some decent quotes included in the book, and I decided that I ought to post a post with some sample quotes here as it would be a relatively easy post to write. Do note while reading this post that the book had a lot of bad quotes, so you should not take the sample quotes I’ve posted below to be representative of the book’s coverage in general.
i. “The aim of science is to seek the simplest explanation of complex facts. We are apt to fall into the error of thinking that the facts are simple because simplicity is the goal of our quest. The guiding motto in the life of every natural philosopher should be “Seek simplicity and distrust it.”” (Alfred North Whitehead)
ii. “Poor data and good reasoning give poor results. Good data and poor reasoning give poor results. Poor data and poor reasoning give rotten results.” (Edmund C. Berkeley)
iii. “By no process of sound reasoning can a conclusion drawn from limited data have more than a limited application.” (J.W. Mellor)
iv. “The energy produced by the breaking down of the atom is a very poor kind of thing. Anyone who expects a source of power from the transformation of these atoms is talking moonshine.” (Ernest Rutherford, 1933).
v. “An experiment is a question which science poses to Nature, and a measurement is the recording of Nature’s answer.” (Max Planck)
vi. “A fact doesn’t have to be understood to be true.” (Heinlein)
vii. “God was invented to explain mystery. God is always invented to explain those things that you do not understand. Now, when you finally discover how something works, you get some laws which you’re taking away from God; you don’t need him anymore. But you need him for the other mysteries. So therefore you leave him to create the universe because we haven’t figured that out yet; you need him for understanding those things which you don’t believe the laws will explain, such as consciousness, or why you only live to a certain length of time – life and death – stuff like that. God is always associated with those things that you do not understand.” (Feynman)
viii. “Hypotheses are the scaffolds which are erected in front of a building and removed when the building is completed. They are indispensable to the worker; but he must not mistake the scaffolding for the building.” (Goethe)
ix. “We are to admit no more cause of natural things than such as are both true and sufficient to explain their appearances.” (Newton)
x. “It is the province of knowledge to speak and it is the privilege of wisdom to listen.” (Oliver Wendell Holmes)
xi. “Light crosses space with the prodigious velocity of 6,000 leagues per second.
La Science Populaire
April 28, 1881″
“A typographical error slipped into our last issue that is important to correct. The speed of light is 76,000 leagues per hour – and not 6,000.
La Science Populaire
May 19, 1881″
“A note correcting a first error appeared in our issue number 68, indicating that the speed of light is 76,000 leagues per hour. Our readers have corrected this new error. The speed of light is approximately 76,000 leagues per second.
La Science Populaire
xii. “All models are wrong but some are useful.” (G. E. P. Box)
xiii. “the downward movement of a mass of gold or lead, or of any other body endowed with weight, is quicker in proportion to its size.” (Aristotle)
xiv. “those whom devotion to abstract discussions has rendered unobservant of the facts are too ready to dogmatize on the basis of a few observations” (-ll-).
xv. “it may properly be asked whether science can be undertaken without taking the risk of skating on the possibly thin ice of supposition. The important thing to know is when one is on the more solid ground of observation and when one is on the ice.” (W. M. O’Neil)
xvi. “If I could remember the names of all these particles, I’d be a botanist.” (Enrico Fermi)
xvii. “Theoretical physicists are accustomed to living in a world which is removed from tangible objects by two levels of abstraction. From tangible atoms we move by one level of abstraction to invisible fields and particles. A second level of abstraction takes us from fields and particles to the symmetry-groups by which fields and particles are related. The superstring theory takes us beyond symmetry-groups to two further levels of abstraction. The third level of abstraction is the interpretation of symmetry-groups in terms of states in ten-dimensional space-time. The fourth level is the world of the superstrings by whose dynamical behavior the states are defined.” (Freeman Dyson)
xviii. “Space tells matter how to move . . . and matter tells space how to curve.” (John Wheeler)
xix. “the universe is not a rigid and inimitable edifice where independent matter is housed in independent space and time; it is an amorphous continuum, without any fixed architecture, plastic and variable, constantly subject to change and distortion. Wherever there is matter and motion, the continuum is disturbed. Just as a fish swimming in the sea agitates the water around it, so a star, a comet, or a galaxy distorts the geometry of the space-time through which it moves.” (Lincoln Barnett)
xx. “most physicists today place the probability of the existence of tachyons only slightly higher than the existence of unicorns” (Nick Herbert).
I was debating whether to post this, but considering how long it’s been since my last post I decided to do it. A large number of lectures have recently been uploaded by the Institute for Advanced Studies, and despite the fact that most of my ‘blogging-related activities’ these days relate to book reading I have watched a few of those lectures, and so I decided to post a couple of the lectures here:
I liked this lecture. Part II of the lecture in particular, starting around the 38 minute mark, dealt with stuff reasonably closely related to things I’d read about before (‘relatively’…) recently, back when I read Lammer’s text (blog coverage here); so although I didn’t remember the stuff covered in Lammer’s text in too much detail, it was definitely helpful to have worked with this stuff before. However I do believe you can watch the lecture and sort of understand what she’s talking about without knowing a great deal about these topics, at least if you don’t care too much about understanding all the details (I’d note that there are a lot of things going on ‘behind the scenes’ here, and that you can say a lot of stuff about topics closely related to this talk, like outgassing processes and how they relate to things like volcanism as well as e.g. the dynamic interactions between atmospheric molecules and the solar wind taking place in the early stages of stellar evolution). As is always the case for IAS lectures it’s really hard to hear the questions being asked and that’s annoying, but actually I think miss Schilchting is reasonably good at repeating the question or sort of answer them in a way that enables you to gather what’s ‘going on’; at least the fact that you can’t hear the questions is in my opinion a somewhat bigger problem in the lecture below (relatedly you can actually also see where the laser pointer is pointing in this lecture, at least some of the time – you can’t in the lecture below).
As mentioned this one was harder to follow, at least for me.
I hope to find time to blog a bit more in the days to come. One of several reasons why I’ve not blogged more than I have during the last weeks is that I recently realized that if I put in a bit of effort I’d be able to reach 150 books this year (I’m currently at 143 books, but very close to 144), with 50 non-fiction books (I think going for 52 would be a bit too much, but I’m not ruling it out yet – I’m currently at 47 non-fiction books (…but very close to 48)). I should note that I update the book post to which I link above much more often than I update ‘the blog’ in general with new posts. The reason why the ‘read 150 books this year goal’ is relevant is of course that every time I blog a book here on the blog, this takes away a substantial amount of time which I can’t spend actually reading books. Goodreads incidentally have recently made a nice ‘book of the year’ profile where you can see more details about the books I’ve read etc. From that profile I realized that my implicit working goal of reading 100 pages/day over the year has already been met (I’m currently at ~42.000 pages).
“A commonplace argument in contemporary writing on trust is that we would all be better off if we were all more trusting, and therefore we should all trust more […] Current writings commonly focus on trust as somehow the relevant variable in explaining differences across cases of successful cooperation. Typically, however, the crucial variable is the trustworthiness of those who are to be trusted or relied upon. […] It is not trust per se, but trusting the right people that makes for successful relationships and happiness.”
“If we wish to understand the role of trust in society […], we must get beyond the flaccid – and often wrong – assumption that trust is simply good. This supposition must be heavily qualified, because trusting the malevolent or the radically incompetent can be foolish and often even grossly harmful. […] trust only make[s] sense in dealings with those who are or who could be induced to be trustworthy. To trust the untrustworthy can be disastrous.”
That it’s stupid to trust people who cannot be trusted should in my opinion be blatantly obvious, yet somehow to a lot of people it doesn’t seem to be at all obvious; in light of this problem (…I maintain that this is indeed a problem) the above observations are probably among the most important ones included in Hardin’s book. The book includes some strong criticism of much of the current/extant literature on trust. The two most common fields of study within this area of research are game-theoretic ‘trust games’, which according to the author are ill-named as they don’t really seem to be dealing much, if at all, with the topic of trust, and (poor) survey research which asks people questions which are hard to answer and tend to yield answers which are even harder to interpret. I have included below a few concluding remarks from the chapter on these topics:
“Both of the current empirical research programs on trust are largely misguided. The T-games [‘trust-games’], as played […] do not elicit or measure anything resembling ordinary trust relations; and their findings are basically irrelevant to the modeling and assessment of trust and trustworthiness. The only thing that relates the so-called trust game […] to trust is its name, which is wrong and misleading. Survey questions currently in wide use are radically unconstrained. They therefore force subjects to assume the relevant degrees of constraint, such as how costly the risk of failed cooperation would be. […] In sum, therefore, there is relatively little to learn about trust from these two massive research programs. Without returning their protocols to address standard conceptions of trust, they cannot contribute much to understanding trust as we generally know it, and they cannot play a very constructive role in explaining social behavior, institutions, or social and political change. These are distressing conclusions because both these enterprises have been enormous, and in many ways they have been carried out with admirable care.”
There is ‘relatively little to learn about trust from these two massive research programs’, but one to me potentially important observation, hidden away in the notes at the end of the book, is perhaps worth mentioning here: “There is a commonplace claim that trust will beget trustworthiness […] Schotter [as an aside this guy was incidentally the author of the Micro textbook we used in introductory Microeconomics] and Sopher (2006) do not find this to be true in game experiments that they run, while they do find that trustworthiness (cooperativeness in the play of games) does beget trust (or cooperation).”
There were a few parts of the coverage which confused me somewhat until it occurred to me that the author might not have read Boyd and Richerson, or other people who might have familiarized him with their line of thinking and research (once again, you should read Boyd and Richerson).
Moving on, a few remarks on social capital:
“Like other forms of capital and human capital, social capital is not completely fungible but may be specific to certain activities. A given form of social capital that is valuable in facilitating certain actions may be useless or even harmful for others. […] [A] mistake is the tendency to speak of social capital as though it were a particular kind of thing that has generalized value, as money very nearly does […] it[‘s value] must vary in the sense that what is functional in one context may not be in another.”
It is important to keep in mind that trust which leads to increased cooperation can end up leading to both good outcomes and bad:
“Widespread customs and even very local practices of personal networks can impose destructive norms on people, norms that have all of the structural qualities of interpersonal capital. […] in general, social capital has no normative valence […] It is generally about means for doing things, and the things can be hideously bad as well as good, although the literature on social capital focuses almost exclusively on the good things it can enable and it often lauds social capital as itself a wonderful thing to develop […] Community and social capital are not per se good. It is a grand normative fiction of our time to suppose that they are.”
The book has a chapter specifically about trust on the internet which related to the coverage included in Barak et al.‘s book, a publication which I have unfortunately neglected to blog (this book of course goes into a lot more detail). A key point in that chapter is that the internet is not really all that special in terms of these things, in the sense that to the extent that it facilitates coordination etc., it can be used to accomplish beneficial things as well as harmful things – i.e. it’s also neutrally valenced. Barak et al.‘s book has a lot more stuff about how this medium impacts communication and optimal communication strategies etc., which links in quite a bit with trust aspects, but I won’t go into this stuff here and I’m pretty sure I’ve covered related topics before here on the blog, e.g. back when I covered Hargie.
The chapter about terrorism and distrust had some interesting observations. A few quotes:
“We know from varied contexts that people can have a more positive view of individuals from a group than they have of the group.”
“Mere statistical doubt in the likely trustworthiness of the members of some identifiable group can be sufficient to induce distrust of all members of the group with whom one has no personal relationship on which to have established trust. […] This statistical doubt can trump relational considerations and can block the initial risk-taking that might allow for a test of another individual’s trustworthiness by stereotyping that individual as primarily a member of some group. If there are many people with whom one can have a particular beneficial interaction, narrowing the set by excluding certain stereotypes is efficient […] Unfortunately, however, excluding very systematically on the basis of ethnicity or race becomes pervasively destructive of community relations.”
One thing to keep in mind here is that people’s stereotypes are often quite accurate. When groups don’t trust each other it’s always a lot of fun to argue about who’s to blame for that state of affairs, but it’s important here to keep in mind that both groups will always have mental models of both the in-group and the out-group (see also the coverage below). Also it should be kept in mind that to the extent that people’s stereotypes are accurate, blaming stereotyping behaviours for the problems of the people who get stereotyped is conceptually equivalent to blaming people for discriminating against untrustworthy people by not trusting people who are not trustworthy. You always come back to the problem that what’s at the heart of the matter is never just trust, but rather trustworthiness. To the extent that the two are related, trust follows trustworthiness, not the other way around.
“There’s a fairly extensive literature on so-called generalized trust, which is trust in the anonymous or general other person, including strangers, whom we might encounter, perhaps with some restrictions on what isues would come under that trust. […] [Generalized trust] is an implausible notion. In any real-world context, I trust some more than others and I trust any given person more about some things than about others and more in some contexts than in others. […] Whereas generalized trust or group-generalized trust makes little or no sense (other than as a claim of optimism), group-generalized distrust in many contexts makes very good sense. If you were Jewish, Gypsy, or gay, you had good reason to distrust all officers of the Nazi state and probably most citizens in Nazi Germany as well. American Indians of the western plains had very good reason to distrust whites. During Milosevic’s wars and pogroms, Serbs, Croatians, and Muslims in then Yugoslavia had increasingly good reasons to distrust most members of the other groups, especially while the latter were acting as groups. […] In all of these cases, distrust is defined by the belief that members of the other groups and their representatives are hostile to one’s interests. Trust relationships between members of these various groups are the unusual cases that require explanation; the relatively group-generalized distrust is easy to understand and justify.”
“In the current circumstances of mostly Arab and Islamic terrorism against israel and the West and much of the rest of the world, it is surely a very tiny fraction of all Arabs and Islamists who are genuinely a threat, but the scale of their threat may make many Israelis and westerners wary of virtually all Arabs and Islamists […] many who are not prospects for taking terrorist action evidently sympathize with and even support these actions”
“When cooperation is organized by communal norms, it can become highly exclusionary, so that only members of the community can have cooperative relations with those in the community. In such a case, the norms of cooperativeness are norms of exclusion […] For many fundamentalist groups, continued loyalty to the group and its beliefs is secured by isolating the group and its members from many other influences so that relations within the community are governed by extensive norms of exclusion. When this happens, it is not only trust relations but also basic beliefs that are constrained. If we encounter no one with contrary beliefs our own beliefs will tend to prevail by inertia and lack of questioning and they will be reinforced by our secluded, exclusionary community. There are many strong, extreme beliefs about religious issues as well as about many other things. […] The two matters for which such staunch loyalty to unquestioned beliefs are politically most important are probably religious and nationalist commitments […] Such beliefs are often maintained by blocking our alternative views and by sanctioning those within the group who stray. […] Narrowing one’s associations to others in an isolated extremist group cripples one’s epistemology by blocking out general questioning of the group’s beliefs […] To an outsider those beliefs might be utterly crazy. Indeed, virtually all strong religious beliefs sound crazy or silly to those who do not share them. […] In some ways, the internet allows individuals and small groups to be quite isolated while nevertheless maintaining substantial contact with others of like mind. Islamic terrorists in the West can be almost completely isolated individually while maintaining nearly instant, frequent contact with other and with groups in the Middle East, Pakistan, or Afghanistan, as well as with groups of other potential terrorists in target nations.”
This is an excellent book. I decided to include in this post the entire book description included on goodreads, even if it’s somewhat long, because I thought the description gave a good overview of the topics covered in this book:
“Providing the most up-to-date research and current clinical knowledge of diabetic bone disease and the challenges still facing the research and clinical care communities, this book unites insights from endocrinology and orthopedics to create a truly unique text. The first part covers clinical and pre-clinical applications and research. The first two chapters present the clinical and epidemiological data about diabetic bone disease, evaluated and reviewed for type 1 and type 2, respectively. This is followed by discussions of how the propensity to fracture in diabetic bone disease can impact fracture risk assessments and how it can be adjusted for using current clinically relevant fracture risk models. A comprehensive overview of orthopedic complications observed in diabetes is next, as well as a focus on the consequences of diabetes on periodontal disease. Other topics include the utility of skeletal biomarkers in assessing diabetic bone disease, how drugs used to treat diabetes may also have skeletal consequences, and the possibility that diabetes may fundamentally impact early progenitor cells of various bone lineages and thus globally impact bone. The second part covers biomechanics and bone quality in diabetes: how diabetes ultimately may impact the architecture, integrity, and quality of bone. Utilizing the expertise of top researcher and clinicians in diabetic bone disease in one comprehensive text, this volume will be a useful and thought-provoking resource for endocrinologists and orthopedic surgeons alike.”
I would note that the book is also a useful and thought-provoking resource if you’re just a random diabetic who happens to know enough about medicine and related topics to make sense of a book like this one – i.e. if you’re someone like me. A few related observations from the book’s preface:
“Historically, most attention has been focused on four major complications known to afflict many individuals with T1DM and T2DM: retinopathy, neuropathy, nephropathy, and cardiovascular disease. However, epidemiological data now show that other tissues and organs may be significantly impacted by the diabetic state—and the skeletal system is now emerging as a primary target of diabetes-mediated damage (i.e., diabetic bone disease).
Studies have demonstrated that osteopenia and osteoporosis may be frequent complications of T1D, both in children and adults, and that T1D is associated with decreased bone density and increased fracture risk. In contrast to T1D, T2D has typically not been associated with osteopenia or osteoporosis and, in fact, has been more often associated with increased BMD [bone mineral density]. However, newer data show that bone quality and bone microarchitecture may be compromised in both conditions, suggesting that underlying mechanisms related to increased risk to fracture may be contributory to both forms of diabetes.
In this volume, we provide the reader with up-to-date information about what is currently known about diabetic bone disease and what are the challenges still facing the research and clinical care communities.”
This was a topic about which I knew next to nothing, and one of emotional responses I had early on to some of the coverage in the book was to think along the lines of: ‘Ah, type 1 diabetes, the gift that keeps on giving…’ or perhaps: ‘How was I not told this???’ It reminded me a bit of how I felt back when I realized some years ago that my diabetes was probably also messing with my lungs, without me knowing about it and despite nobody having told me anything about that (for details on that topic, see e.g. this paper). As far as I can remember, bone health has never come up during conversations I have had over the years in the past with endocrinologists or diabetes nurses, nor has it ever been discussed in detail in publications I’ve read on diabetes-related topics; the closest I’ve got has probably been remarks about individuals developing diabetics during childhood being slightly shorter than non-diabetics on average, due to (non-specific) disease-related adverse effects on growth during childhood. Relevant mechanisms have not been discussed in any detail, and actually what I had read on the topic of diabetes and growth had basically lead me to believe that a slight growth disadvantage was really all there was to this topic, as a potential interaction between diabetes status and osteoporosis risk was never touched upon in these publications. To give a great illustrative example, Sperling et al.‘s comprehensive textbook (~600 pages) about type 1 diabetes includes exactly 3 hits for osteoporosis in the text, all of which relate to very specific subtopics and none of which even remotely relate to the highly increased risk of fractures which type 1 diabetes in particular confers – the authors of that text clearly had no idea that type 1 diabetes dramatically increases the risk of fractures and poor bone health; there are zero indications to the contrary. It’s probably not uncommon to see important information in textbooks which people forget about in clinical practice (perhaps because the people working in clinical practice read different textbooks, in which this information was not included…), but it’s certainly less common to see important information not included in textbooks because the textbook authors simply don’t know about them. It seems highly likely to me that a lot of health care providers involved in diabetes care currently do not know anything about the topics discussed in this publication; I hope this state of affairs will change in the future.
As also noted in the comments above, the relationship between diabetes and bone health is complicated and interacts with type; type 1 seems to be much worse for the bones than is type 2, and the relationship between in particular type 2 diabetes and bone health is not at all simple. Type 2 diabetics tend to have both some elevated non-diabetes-related risk factors for fractures (in one chapter the authors thus list in that category obesity, reduced muscle quality, poor balance, and falls – e.g. but not only hypoglycemia-related) and some diabetes-specific risk factors ((/very) poor glycemic control probably increases risk (but see also below), duration of disease increases risk, medications – e.g. the thiazolidinedione drug class used to treat type 2 diabetes), but these don’t fully account for the increased risk.
Most of the standard metrics used to assess fracture risk, such as FRAX, do not take diabetes status into account, which is a problem – “studies indicate that FRAX systematically underestimates fracture risk in patients with T2DM” (this problem is not just related to FRAX, thus elsewhere in the publication it is noted more generally that: “fracture prediction tools underestimate fracture risk in diabetes”). The only one of the widely used risk assessment tools which does take diabetes status into account is the QFracture tool, but this tool “has not been specifically evaluated with regard to calibration in individuals with diabetes”; so there is a lot of uncertainty here. This state of affairs is of course hardly ideal, especially not considering how the number of type 2 diabetics is projected to increase over time in the years to come. It is worth keeping in mind that the total population prevalence of type 2 can be deceiving people here into thinking this is less of a problem than it really is, as most people at increased risk of fractures are old people, and type 2 incidence/prevalence increases with age: “Type 2 diabetes affects over 25 % of older adults in the United States, including diagnosed and undiagnosed cases .” The hip fracture estimates included in Vestergaard’s meta-review discussed below indicate a relative risk of hip-fracture of ~1.4 in the type 2 diabetic sub-population, and if you multiply that number by the 25% prevalence among elderly people in the US, that’s more than a third of all fractures in older adults. That’s a lot of people, and a lot of risk not well accounted for.
A problem related to the above observations in the context of type 2 diabetes (and most of the research that has been done in this area has been done on type 2 diabetes, for reasons which should be obvious (“type 1 diabetes mellitus (T1D) accounts for <10 % of all diabetes […] In the USA, prevalence of T1D has recently been estimated at 1 in every 433 youth <20 years of age”)) is that dual-energy X-ray absorptiometry (DXA), a standard way to measure bone mineral density also used to diagnose osteoporosis, does not ‘pick up on’ the excess risk associated with T2DM; in type 2 individuals risk is elevated even when taking DXA measurements into account (this fact may actually be one argument why the QFracture tool may not be bad at all to apply to people in this patient subgroup; QFracture does not include DXA numbers, and if a substantial proportion of the risk is unrelated to the DXA estimates in type 2 anyway then maybe they’re not that important to include). The arguably poor performance of DXA in the context of fracture risk in type 2 diabetes have lead to the development of other tools which might be better at assessing risk in this patient population, and the authors of some of the later chapters of the book talk in some detail about these tools and the results derived from related studies using these tools. It should perhaps be noted in the context of DXA and bone mineral density numbers that one of the clear differences between type 1 and type 2 here is that bone mineral density tends to be decreased in type 1 diabetes, whereas it’s usually if anything increased in type 2 (but the increased, or at least not lowered, bone mineral density in type 2 does not translate into a lower risk of fracture; risk is still elevated, which is what is surprising and not easy to fully account for).
An interesting aspect of the coverage was that the relationship between glycemic control and bone health seems to not be completely clear; to me the coverage of this topic throughout the various chapters (many chapters cover closely related topics and there’s some coverage overlap, but I didn’t mind this at all) reminded much more of the typical coverage you see in publications discussing how the risk of macrovascular complications relate to glycemic control (…’it’s complicated’) than it reminded me of how the risk of microvascular complications relate to glycemic control (…’hyperglycemia increases risk and there’s a dose-response relationship between complication risk and the level of hyperglycemia’). One problem is that low Hba1c may increase the fall risk because of an increased risk of hypoglycemic episodes, increasing risk at the lower end of the spectrum.
The book has a lot of stuff about the specifics of what might be going on at the cellular level and so on, but I won’t talk much about that here even if I found it interesting (it would take a lot of time to go over the details here); one key point to take take away from that part of the coverage should however be mentioned here, and that is that that stuff thoroughly convinced me that there’s no way the increased fracture risks observed in the various epidemiological studies presented at the beginning of the publication are flukes. There are good reasons to think that diabetes may be bad for the bones, quite aside from the reason that they seem to break their bones more often than other people do.
I have included some data and key observations from the book below. As the post is rather long I decided to highlight/bold a few of the most important observations (they’re not bolded in the book).
“In patients with T1D, an increased incidence of osteopenia and osteoporosis has been recognized for over three decades [10–14], occurring not only in adults, but in children as well [15–17]. Many more recent studies have since validated these early findings, demonstrating a reduced bone mineral density (BMD) in T1D [18–22]. Clinical factors associated with lower bone density include: male gender […]; longer duration of disease […]; younger age at diagnosis […]; lower endogenous insulin or C-peptide levels ; low body mass index (BMI) […]; and possibly the presence of chronic diabetes comorbidities or associated autoimmunity . Some studies also suggest that greater longitudinal decrements in BMD occur over time in males . […] In most studies, poor glycemic control does not seem to be strongly associated with a reduced BMD [18–20, 22, 23, 30, 31] […] T1D is […] associated with an increased risk for fracture, higher than the risk in type 2 diabetes (T2D)”
“among risk factors for hip fracture in >33,000 middle-aged adults in Sweden (~25–60 years), the strongest risk factor for both women […] and men […] was diabetes , suggesting that the presence of diabetes was a major risk determinant for this age group. Similar findings had been reported years before in middle-aged Norwegian women and men […] Together, [studies conducted during the last 15 years on type 1 diabetics] demonstrate an unequivocally increased fracture risk at the hip [compared to non-diabetic controls], with most demonstrating a six to ninefold increase in relative risk. […] type I DM patients have hip fractures at a younger age on average, with a mean of 43 for women and 41 for men in one study. Almost 7 % of people with type I DM can be expected to have sustained a hip fracture by age 65  […] Patients with DM and hip fracture are at a higher risk of mortality than patients without DM, with 1-year rates as high as 32 % vs. 13 % of nondiabetic patients […] Though only a very few studies have examined fracture risk at other skeletal sites [51, 54], an increased risk for vertebral fracture is also a consistent finding in studies that have quantified this. […] in one study, an approximate threefold increase in risk for all non-vertebral fractures was reported in men with T1D”.
“studies […] suggest that cumulative changes in bone architecture are beginning early in childhood, particularly in those diagnosed with T1D at very young ages . Compared with nondiabetic children, reductions in BMD [68, 74–78] and bone size, specifically total cross-sectional area (CSA) [73, 79] and cortical area [15, 80], are relatively consistent findings. […] As a whole, […] studies suggest that systemic markers of bone formation in T1D are generally indicative of a condition in which bone formation is reduced. […] Taken together, it would appear that T1D is characterized best as a state of inappropriately lowered bone turnover which exists in conjunction with relative osteoblast dysfunction  and, hence, low bone formation […] serum AGE concentrations are clearly elevated in T1D during childhood , even during preschool and prepubertal years […] skin AGEs […] are increased in children with both T1D and T2D, to the extent that “approximately 4–6 years of diabetes exposure in some children may be sufficient to increase skin AGEs to levels that would naturally accumulate only after ~25 years of chronological aging””.
“diabetic bone has a greater propensity for fracture than is predicted by BMD […] A role for the skeletal accumulation of advanced glycation end products […], chronic hyperglycemia , oxidative stress , and microarchitectural bone defects  have all been proposed, and it is expected that the pathological mechanisms leading to bone fragility in T1D are multifactorial […] Beyond fragility fractures, other skeletal complications also occur disproportionately in persons with T1D, including fracture-healing complications (nonunion, malunion) , Charcot osteoarthropathy , osteomyelitis, and diabetic foot syndrome.”
“In orthopaedics, patients with diabetes have a number of associated disorders, and these present a challenge as many have an increased hospital stay, higher risk of infection, and higher risk of complications after orthopaedic treatment. The orthopaedic-related problems in diabetes are varied, and the true causal links between diabetes and the disorders are largely unknown. […] The incidence of trigger finger [/stenosing tenosynovitis] is 7–20 % of patients with diabetes comparing to only about 1–2 % in nondiabetic patients […] The prevalence of [carpal tunnel syndrome, CTS] in patients with diabetes has been estimated at 11–30 % [130, 133, 153, 156], and is dependent on the duration of diabetes. […] Type I DM patients have a high prevalence of CTS with increasing duration of disease, up to 85 % after 54 years of DM. However the prevalence does not seem to be associated with glycemic control”
“Diabetes increases the severity and risk of periodontitis, the most common lytic disease of bone and a frequent complication of diabetes […] The risk of periodontitis is increased approximately 2–4 times in diabetic versus nondiabetic subjects [4, 47]. In one study, periodontitis was found in 60 % of T1DM patients compared to 15 % without diabetes . Patients with diabetes are at higher risk of severe periodontitis compared with nondiabetic subjects […] There is a direct link between persistent hyperglycemia, an exaggerated inflammatory response to periodontal pathogens and periodontal bone loss”.
“Because diabetic bone disease in type 1 diabetes represents a deficit in osteoblast function and bone formation, antiresorptive therapies for osteoporosis (e.g., bisphosphonates, denosumab) may be ineffective in this form of secondary osteoporosis […] Calcium and vitamin D supplementation […] is considered standard-of-care for osteoporosis treatment . Nonetheless, 1 year of calcitriol supplementation in young adults with recent-onset T1D did not significantly change circulating markers of bone turnover […] very little information from comparative effectiveness studies is available on the treatment of osteoporosis in T1D.”
Type 2 does not increase risk nearly as much as does type 1:
“In 2007 Vestergaard published a meta-analysis of hip fracture results that included eight studies and reported an age-adjusted summary relative risk for hip fracture of 1.38 (1.25–1.53), comparing those with and without T2D . This increase in fracture risk with T2D occurred in spite of higher bone density in those with T2D. […] Most [15–21], but not all [22, 23], subsequent studies have reported increased rates of hip fracture with T2D in age-adjusted models. […] Evidence that more frequent falls do not fully account for increased fracture risk with T2D […], combined with evidence from rodent models , has led to the conclusion that diabetic bone is more fragile for a given BMD. Understanding the aspects of bone that are affected by diabetes and that result in fragile bone has been an important focus of research on diabetes and skeletal health.”
“The effect of glycemic control on fracture risk, BMD, and falls remains poorly understood and controversial.”
“Diabetic patients with multiple complications appear to be at higher risk of fracture, but results are mixed for the association between specific complications and fracture.”
“Our current understanding of the pathogenesis of skeletal fragility in [type 2] diabetes suggests a working model […], whereby poor glucose control in patients with T2DM leads to increases in AGEs that have negative effects on osteoblasts, which in turn causes a reduction in bone formation. This defect in bone formation subsequently results in low bone turnover in T2DM patients, which prolongs the lifespan of type I collagen in bone, thereby leaving it particularly vulnerable to damage from increased AGEs. Ultimately, this creates a “vicious cycle” that may contribute to reduced bone quality and increased fracture risk in patients with T2DM.”
As for an overall assessment of the book, I gave the book five stars on goodreads, because it’s basically to a significant extent written the way I’d like Springer publications like this one to be written. The language in one chapter (out of 11) was slightly sub-optimal, but aside from that chapter every single chapter was in my opinion well written, some of them very well written. Frequent discussions of the results of meta-analyses were included in the book. The authors seemed in general to be aware of potential problems with specific interpretations and to me seemed cautious about drawing strong conclusions from the data they had at hand; in terms of the analytical level of the coverage the publication for example included comments about problems with confounding by indication in cross section analyses. There were a couple of places in one of the later chapters where it was slightly difficult for me to figure out ‘what was going on’, but the coverage included in the next chapter of the book clarified these issues; I was not willing to subtract a star because of that.
David Friedman recently asked a related question on SSC (he asked about why there are waiting lists for surgical procedures), and I decided that as I’d read some stuff about these topics in the past I might as well answer his question. The answer turned out to be somewhat long/detailed, and I decided I might as well post some of this stuff here as well. In a way my answer to David’s question provides belated coverage of a book I read last year, Appointment Planning in Outpatient Clinics and Diagnostic Facilities, which I have covered only in very limited detail here on the blog before (the third paragraph of this post is the only coverage of the book I’ve provided here).
Below I’ve tried to cover these topics in a manner which would make it unnecessary to also read David’s question and related comments.
The brief Springer publication Appointment Planning in Outpatient Clinics and Diagnostic Facilities has some basic stuff about operations research and queueing theory which is useful for making sense of resource allocation decisions made in the medical sector. I think this is the kind of stuff you’ll want to have a look at if you want to understand these things better.
There are many variables which are important here and which may help explain why waiting lists are common in the health care sector (it’s not just surgery). The quotes below are from the book:
“In a walk-in system, patients are seen without an appointment. […] The main advantage of walk-in systems is that access time is reduced to zero. […] A huge disadvantage of patients walking in, however, is that the usually strong fluctuating arrival stream can result in an overcrowded clinic, leading to long waiting times, high peaks in care provider’s working pressure, and patients leaving without treatment (blocking). On other moments of time the waiting room will be practically empty […] In regular appointment systems workload can be dispersed, although appointment planning is usually time consuming. A walk-in system is most suitable for clinics with short service times and multiple care providers, such as blood withdrawal facilities and pre-anesthesia check-ups for non-complex patients. If the service times are longer or the number of care providers is limited, the probability that patients experience a long waiting time becomes too high, and a regular appointment system would be justified”
“Sometimes it is impossible to provide walk-in service for all patients, for example when specific patients need to be prepared for their consultation, or if specific care providers are required, such as anesthesiologists [I noted in my reply to David that these remarks seem highly relevant for the surgery context]. Also, walk-in patients who experience a full waiting room upon arrival may choose to come back at a later point in time. To make sure that they do have access at that point, clinics usually give these patients an appointment. This combination of walk-in and appointment patients requires a specific appointment system that satisfies the following requirements:
1. The access time for appointment patients is below a certain threshold
2. The waiting time for walk-in patients is below a certain threshold
3. The number of walk-in patients who are sent away due to crowding is minimized
To satisfy these requirements, an appointment system should be developed to determine the optimal scheduling of appointments, not only on a day level but also on a week level. Developing such an appointment system is challenging from a mathematical perspective. […] Due to the high variability that is usually observed in healthcare settings, introducing stochasticity in the modeling process is very important to obtain valuable and reasonable results.”
“Most elective patients will ultimately evolve into semi-urgent or even urgent patients if treatment is extensively prolonged.” That’s ‘on the one hand’ – but of course there’s also the related ‘on the other hand’-observation that: “Quite often a long waiting list results in a decrease in demand”. Patients might get better on their own and/or decide it’s not worth the trouble to see a service provider – or they might deteriorate.
“Some planners tend to maintain separate waiting lists for each patient group. However, if capacity is shared among these groups, the waiting list should be considered as a whole as well. Allocating capacity per patient group usually results in inflexibility and poor performance”.
“mean waiting time increases with the load. When the load is low, a small increase therein has a minimal effect on the mean waiting time. However, when the load is high, a small increase has a tremendous effect on the mean waiting time. For instance, […] increasing the load from 50 to 55 % increases the waiting time by 10 %, but increasing the load from 90 to 95 % increases the waiting time by 100 % […] This explains why a minor change (for example, a small increase in the number of patients, a patient arriving in a bed or a wheelchair) can result in a major increase in waiting times as sometimes seen in outpatient clinics.”
“One of the most important goals of this chapter is to show that it is impossible to use all capacity and at the same time maintain a short, manageable waiting list. A common mistake is to reason as follows:
Suppose total capacity is 100 appointments. Unused capacity is commonly used for urgent and inpatients, that can be called in last minute. 83 % of capacity is used, so there is on average 17 % of capacity available for urgent and inpatients. The urgent/inpatient demand is on average 20 appointments per day. Since 17 appointments are on average not used for elective patients, a surplus capacity of only three appointments is required to satisfy all patient demand.
Even though this is true on average, more urgent and inpatient capacity is required. This is due to the variation in the process; on certain days 100 % of capacity is required to satisfy elective patient demand, thus leaving no room for any other patients. Furthermore, since 17 slots are dedicated to urgent and inpatients, only 83 slots are available for elective patients, which means that ρ is again equal to 1, resulting in an uncontrollable waiting list.” [ρ represents the average proportion of time which the server/service provider is occupied – a key stability requirement is that ρ is smaller than one; if it is not, the length of the queue becomes unstable/explodes. See also this related link].
“The challenge is to make a trade-off between maintaining a waiting list which is of acceptable size and the amount of unused capacity. Since the focus in many healthcare facilities is on avoiding unused capacity, waiting lists tend to grow until “something has to be done.” Then, temporarily surplus capacity is deployed, which is usually more expensive than regular capacity […]. Even though waiting lists have a buffer function (i.e., by creating a reservoir of patients that can be planned when demand is low) it is unavoidable that, even in well-organized facilities, over a longer period of time not all capacity is used.”
I think one way to think about the question of whether it makes sense to have a waiting list or whether you can ‘just use the price variable’ is that if it is possible for you as a provider to optimize over both the waiting time variable and the price variable (i.e., people demanding the service find some positive waiting time to be acceptable when it is combined with a non-zero price reduction), the result you’re going to get is always going to be at least as good as an option where you only have the option of optimizing over price – not including waiting time in the implicit pricing mechanism can be thought of as in a sense a weakly dominated strategy.
A lot of the planning stuff relates to how to handle variable demand, and input heterogeneities can be thought of as one of many parameters which may be important to take into account in the context of how best to deal with variable demand; surgeons aren’t perfect substitutes. Perhaps neither are nurses, or different hospitals (relevant if you’re higher up in the decision making hierarchy). An important aspect is the question of whether a surgeon (or a doctor, or a nurse…) might be doing other stuff instead of surgery during down-periods, and what might be the value of that other stuff s/he might be doing instead. In the surgical context, not only is demand variable over time, there are also issues such as that many different inputs need to be coordinated; you need a surgeon and a scrub nurse and an anesthesiologist. The sequential and interdependent nature of many medical procedures and inputs is likely also a factor in terms of adding complexity; whether a condition requires treatment or not, and/or which treatment may be required, may depend upon the results of a test which has to be analyzed before the treatment is started, and so you for example can’t switch the order of test and treatment, or for that matter treat patient X based on patient Y’s test results; there’s some built-in inflexibility here at the outset. This type of thing also means there are more nodes in the network, and more places where things can go wrong, resulting in longer waiting times than planned.
I think the potential gains in terms of capacity utilization, risk reduction and increased flexibility to be derived from implementing waiting schemes of some kind in the surgery context would mediate strongly against a model without waiting lists, and I think that the surgical field is far from unique in that respect in the context of medical care provision.
“Statistical considerations arise in virtually all areas of science and technology and, beyond these, in issues of public and private policy and in everyday life. While the detailed methods used vary greatly in the level of elaboration involved and often in the way they are described, there is a unity of ideas which gives statistics as a subject both its intellectual challenge and its importance […] In this book we have aimed to discuss the ideas involved in applying statistical methods to advance knowledge and understanding. It is a book not on statistical methods as such but, rather, on how these methods are to be deployed […] We are writing partly for those working as applied statisticians, partly for subject-matter specialists using statistical ideas extensively in their work and partly for masters and doctoral students of statistics concerned with the relationship between the detailed methods and theory they are studying and the effective application of these ideas. Our aim is to emphasize how statistical ideas may be deployed fruitfully rather than to describe the details of statistical techniques.”
I gave the book five stars, but as noted in my review on goodreads I’m not sure the word ‘amazing’ is really fitting – however the book had a lot of good stuff and it had very little stuff for me to quibble about, so I figured it deserved a high rating. The book deals to a very large extent with topics which are in some sense common to pretty much all statistical analyses, regardless of the research context; formulation of research questions/hypotheses, data search, study designs, data analysis, and interpretation. The authors spend quite a few pages talking about hypothesis testing but on the other hand no pages talking about statistical information criteria, a topic with which I’m at this point at least reasonably familiar, and I figure if I had been slightly more critical I’d have subtracted a star for this omission – however I have the impression that I’m at times perhaps too hard on non-fiction books on goodreads so I decided not to punish the book for this omission. Part of the reason why I gave the book five stars is also that I’ve sort of wanted to read a book like this one for a while; I think in some sense it’s the first one of its kind I’ve read. I liked the way the book was structured.
Below I have added some observations from the book, as well as a few comments (I should note that I have had to leave out a lot of good stuff).
“When the data are very extensive, precision estimates calculated from simple standard statistical methods are likely to underestimate error substantially owing to the neglect of hidden correlations. A large amount of data is in no way synonymous with a large amount of information. In some settings at least, if a modest amount of poor quality data is likely to be modestly misleading, an extremely large amount of poor quality data may be extremely misleading.”
“For studies of a new phenomenon it will usually be best to examine situations in which the phenomenon is likely to appear in the most striking form, even if this is in some sense artificial or not representative. This is in line with the well-known precept in mathematical research: study the issue in the simplest possible context that is not entirely trivial, and later generalize.”
“It often […] aids the interpretation of an observational study to consider the question: what would have been done in a comparable experiment?”
“An important and perhaps sometimes underemphasized issue in empirical prediction is that of stability. Especially when repeated application of the same method is envisaged, it is unlikely that the situations to be encountered will exactly mirror those involved in setting up the method. It may well be wise to use a procedure that works well over a range of conditions even if it is sub-optimal in the data used to set up the method.”
“Many investigations have the broad form of collecting similar data repeatedly, for example on different individuals. In this connection the notion of a unit of analysis is often helpful in clarifying an approach to the detailed analysis. Although this notion is more generally applicable, it is clearest in the context of randomized experiments. Here the unit of analysis is that smallest subdivision of the experimental material such that two distinct units might be randomized (randomly allocated) to different treatments. […] In general the unit of analysis may not be the same as the unit of interpretation, that is to say, the unit about which conclusions are to drawn. The most difficult situation is when the unit of analysis is an aggregate of several units of interpretation, leading to the possibility of ecological bias, that is, a systematic difference between, say, the impact of explanatory variables at different levels of aggregation. […] it is important to identify the unit of analysis, which may be different in different parts of the analysis […] on the whole, limited detail is needed in examining the variation within the unit of analysis in question.”
The book briefly discusses issues pertaining to the scale of effort involved when thinking about appropriate study designs and how much/which data to gather for analysis, and notes that often associated costs are not quantified – rather a judgment call is made. An important related point is that e.g. in survey contexts response patterns will tend to depend upon the quantity of information requested; if you ask for too much, few people might reply (…and perhaps it’s also the case that it’s ‘the wrong people’ that reply? The authors don’t touch upon the potential selection bias issue, but it seems relevant). A few key observations from the book on this topic:
“the intrinsic quality of data, for example the response rates of surveys, may be degraded if too much is collected. […] sampling may give higher [data] quality than the study of a complete population of individuals. […] When researchers studied the effect of the expected length (10, 20 or 30 minutes) of a web-based questionnaire, they found that fewer potential respondents started and completed questionnaires expected to take longer (Galesic and Bosnjak, 2009). Furthermore, questions that appeared later in the questionnaire were given shorter and more uniform answers than questions that appeared near the start of the questionnaire.”
Not surprising, but certainly worth keeping in mind. Moving on…
“In general, while principal component analysis may be helpful in suggesting a base for interpretation and the formation of derived variables there is usually considerable arbitrariness involved in its use. This stems from the need to standardize the variables to comparable scales, typically by the use of correlation coefficients. This means that a variable that happens to have atypically small variability in the data will have a misleadingly depressed weight in the principal components.”
The book includes a few pages about the Berkson error model, which I’d never heard about. Wikipedia doesn’t have much about it and I was debating how much to include about this one here – I probably wouldn’t have done more than including the link here if the wikipedia article actually covered this topic in any detail, but it doesn’t. However it seemed important enough to write a few words about it. The basic difference between the ‘classical error model’, i.e. the one everybody knows about, and the Berkson error model is that in the former case the measurement error is statistically independent of the true value of X, whereas in the latter case the measurement error is independent of the measured value; the authors note that this implies that the true values are more variable than the measured values in a Berkson error context. Berkson errors can e.g. happen in experimental contexts where levels of a variable are pre-set by some target, for example in a medical context where a drug is supposed to be administered each X hours; the pre-set levels might then be the measured values, and the true values might be different e.g. if the nurse was late. I thought it important to mention this error model not only because it’s a completely new idea to me that you might encounter this sort of error-generating process, but also because there is no statistical test that you can use to figure out if the standard error model is the appropriate one, or if a Berkson error model is better; which means that you need to be aware of the difference and think about which model works best, based on the nature of the measuring process.
Let’s move on to some quotes dealing with modeling:
“while it is appealing to use methods that are in a reasonable sense fully efficient, that is, extract all relevant information in the data, nevertheless any such notion is within the framework of an assumed model. Ideally, methods should have this efficiency property while preserving good behaviour (especially stability of interpretation) when the model is perturbed. Essentially a model translates a subject-matter question into a mathematical or statistical one and, if that translation is seriously defective, the analysis will address a wrong or inappropriate question […] The greatest difficulty with quasi-realistic models [as opposed to ‘toy models’] is likely to be that they require numerical specification of features for some of which there is very little or no empirical information. Sensitivity analysis is then particularly important.”
“Parametric models typically represent some notion of smoothness; their danger is that particular representations of that smoothness may have strong and unfortunate implications. This difficulty is covered for the most part by informal checking that the primary conclusions do not depend critically on the precise form of parametric representation. To some extent such considerations can be formalized but in the last analysis some element of judgement cannot be avoided. One general consideration that is sometimes helpful is the following. If an issue can be addressed nonparametrically then it will often be better to tackle it parametrically; however, if it cannot be resolved nonparametrically then it is usually dangerous to resolve it parametrically.”
“Once a model is formulated two types of question arise. How can the unknown parameters in the model best be estimated? Is there evidence that the model needs modification or indeed should be abandoned in favour of some different representation? The second question is to be interpreted not as asking whether the model is true [this is the wrong question to ask, as also emphasized by Burnham & Anderson] but whether there is clear evidence of a specific kind of departure implying a need to change the model so as to avoid distortion of the final conclusions. […] it is important in applications to understand the circumstances under which different methods give similar or different conclusions. In particular, if a more elaborate method gives an apparent improvement in precision, what are the assumptions on which that improvement is based? Are they reasonable? […] the hierarchical principle implies, […] with very rare exceptions, that models with interaction terms should include also the corresponding main effects. […] When considering two families of models, it is important to consider the possibilities that both families are adequate, that one is adequate and not the other and that neither family fits the data.” [Do incidentally recall that in the context of interactions, “the term interaction […] is in some ways a misnomer. There is no necessary implication of interaction in the physical sense or synergy in a biological context. Rather, interaction means a departure from additivity […] This is expressed most explicitly by the requirement that, apart from random fluctuations, the difference in outcome between any two levels of one factor is the same at all levels of the other factor. […] The most directly interpretable form of interaction, certainly not removable by [variable] transformation, is effect reversal.”]
“The p-value assesses the data […] via a comparison with that anticipated if H0 were true. If in two different situations the test of a relevant null hypothesis gives approximately the same p-value, it does not follow that the overall strengths of the evidence in favour of the relevant H0 are the same in the two cases.”
“There are […] two sources of uncertainty in observational studies that are not present in randomized experiments. The first is that the ordering of the variables may be inappropriate, a particular hazard in cross-sectional studies. […] if the data are tied to one time point then any presumption of causality relies on a working hypothesis as to whether the components are explanatory or responses. Any check on this can only be from sources external to the current data. […] The second source of uncertainty is that important explanatory variables affecting both the potential cause and the outcome may not be available. […] Retrospective explanations may be convincing if based on firmly established theory but otherwise need to be treated with special caution. It is well known in many fields that ingenious explanations can be constructed retrospectively for almost any finding.”
“The general issue of applying conclusions from aggregate data to specific individuals is essentially that of showing that the individual does not belong to a subaggregate for which a substantially different conclusion applies. In actuality this can at most be indirectly checked for specific subaggregates. […] It is not unknown in the literature to see conclusions such as that there are no treatment differences except for males aged over 80 years, living more than 50 km south of Birmingham and life-long supporters of Aston Villa football club, who show a dramatic improvement under some treatment T. Despite the undoubted importance of this particular subgroup, virtually always such conclusions would seem to be unjustified.” [I loved this example!]
The authors included a few interesting results from an undated Cochrane publication which I thought I should mention. The file-drawer effect is well known, but there are a few other interesting biases at play in a publication bias context. One is time-lag bias, which means that statistically significant results take less time to get published. Another is language bias; statistically significant results are more likely to be published in English publications. A third bias is multiple publication bias; it turns out that papers with statistically significant results are more likely to be published more than once. The last one mentioned is citation bias; papers with statistically significant results are more likely to be cited in the literature.
The authors include these observations in their concluding remarks: “The overriding general principle [in the context of applied statistics], difficult to achieve, is that there should be a seamless flow between statistical and subject-matter considerations. […] in principle seamlessness requires an individual statistician to have views on subject-matter interpretation and subject-matter specialists to be interested in issues of statistical analysis.”
As already mentioned this is a good book. It’s not long, and/but it’s worth reading if you’re in the target group.
ii. “The man who knows everyone’s job isn’t much good at his own.” (-ll-)
iii. “It is amazing what little harm doctors do when one considers all the opportunities they have” (Mark Twain, as quoted in the Oxford Handbook of Clinical Medicine, p.595).
iv. “A first-rate theory predicts; a second-rate theory forbids and a third-rate theory explains after the event.” (Aleksander Isaakovich Kitaigorodski)
v. “[S]ome of the most terrible things in the world are done by people who think, genuinely think, that they’re doing it for the best” (Terry Pratchett, Snuff).
vi. “That was excellently observ’d, say I, when I read a Passage in an Author, where his Opinion agrees with mine. When we differ, there I pronounce him to be mistaken.” (Jonathan Swift)
vii. “Death is nature’s master stroke, albeit a cruel one, because it allows genotypes space to try on new phenotypes.” (Quote from the Oxford Handbook of Clinical Medicine, p.6)
viii. “The purpose of models is not to fit the data but to sharpen the questions.” (Samuel Karlin)
ix. “We may […] view set theory, and mathematics generally, in much the way in which we view theoretical portions of the natural sciences themselves; as comprising truths or hypotheses which are to be vindicated less by the pure light of reason than by the indirect systematic contribution which they make to the organizing of empirical data in the natural sciences.” (Quine)
x. “At root what is needed for scientific inquiry is just receptivity to data, skill in reasoning, and yearning for truth. Admittedly, ingenuity can help too.” (-ll-)
xi. “A statistician carefully assembles facts and figures for others who carefully misinterpret them.” (Quote from Mathematically Speaking – A Dictionary of Quotations, p.329. Only source given in the book is: “Quoted in Evan Esar, 20,000 Quips and Quotes“)
xii. “A knowledge of statistics is like a knowledge of foreign languages or of algebra; it may prove of use at any time under any circumstances.” (Quote from Mathematically Speaking – A Dictionary of Quotations, p. 328. The source provided is: “Elements of Statistics, Part I, Chapter I (p.4)”).
xiii. “We own to small faults to persuade others that we have not great ones.” (Rochefoucauld)
xiv. “There is more self-love than love in jealousy.” (-ll-)
xv. “We should not judge of a man’s merit by his great abilities, but by the use he makes of them.” (-ll-)
xvi. “We should gain more by letting the world see what we are than by trying to seem what we are not.” (-ll-)
xvii. “Put succinctly, a prospective study looks for the effects of causes whereas a retrospective study examines the causes of effects.” (Quote from p.49 of Principles of Applied Statistics, by Cox & Donnelly)
xviii. “… he who seeks for methods without having a definite problem in mind seeks for the most part in vain.” (David Hilbert)
xix. “Give every man thy ear, but few thy voice” (Shakespeare).
xx. “Often the fear of one evil leads us into a worse.” (Nicolas Boileau-Despréaux)
I didn’t finish this book and I didn’t have a lot of nice things to say about it in my review on goodreads, but as I did read roughly half of it and it seemed easy to blog, I figured I might as well cover it here.
I have added some observations from the book and a few comments below:
“While we know that every marriage brings not only promise but substantial risk, to date we know more about the harmful processes in relationships than we do about what makes them work”
“expressions of positivity, especially gratitude, promote relationship maintenance in intimate bonds”
“Baxter and Montgomery (1996) maintain that the closeness of a relationship may be determined by the extent to which the ‘self becomes’ or changes through participation in that relationship, suggesting that boundaries between ‘self’ and ‘other’ are more permeable and fluid in a close, intimate relationship. […] Not surprisingly, this collective sense of an ‘us’ appears to grow stronger with time and age with older couples demonstrating greater levels of we-ness than couples at middle-age”
“It has been demonstrated […] that affirmation by one’s partner that is in keeping with one’s own self-ideal, is associated with better relationship adjustment and stability […]. Moreover, if a spouse’s positive view of his or her mate is more favorable than the mate’s own view, and if the spouse tries to stabilize such positive impressions then, over time, the person’s negative self-view could begin to change for the better […] Perceiving one’s partner as responsive to one’s needs, goals, values and so forth has generally been associated with greater relationship satisfaction and personal well-being […]. The concomitant experience of feeling validated, understood and cared for […] would arguably be that much more imperative when one partner is in distress. Such responsiveness entails the ability “to discern non-verbal cues, and to ‘read between the lines’ about motivations, emotions, and experiences,” […] Being attuned and responsive to non-verbal and para-verbal cues, in turn, is conducive to couple coping because it enables well spouses to be appropriately supportive without having to be explicitly directed or asked.” (I recall thinking that the topic of ‘hidden support’ along these lines was a very important topic to keep in mind in the future when I first read about it. It’s covered in much more detail in one of the previous books I’ve read on related topics, though I can’t recall at the moment if it was in Vangelisti & Perlman, Hargie, or Regan).
“Sexual resilience […] is a term used to describe individuals or couples who are able to withstand, adapt, and find solutions to events and experiences that challenge their sexual relationship.[…] the most common challenges to sexuality include the birth of the first child […]; the onset of a physical or mental illness […]; an emotional blow to the relationship, such as betrayal or hurt; lack of relational intimacy, such as becoming absorbed by other priorities such as career; and changes associated with aging, such as vaginal dryness or erectile dysfunction. […] People who place a relatively low value on sex for physical pleasure and a relatively high value on sex for relational intimacy […] are motivated to engage in sexual activity primarily to feel emotionally close to their partner. […] these individuals may respond to sexual challenges with less distress than those who place a high value on sex for physical pleasure. On an individual level, they are not overly concerned about specific sexual dysfunctions, but are motivated to find alternative ways of continuing to be sexually intimate with their partner, which may or may not include intercourse. […] Facing sexual difficulties with a high value placed on sex for relational intimacy, with strong dyadic adjustment, and with effective and open communication skills primes a couple to respond well to sexual challenges. […] Acceptance, flexibility, and persistence are characteristics most commonly associated with couples who successfully negotiated the challenges to their sexual relationship. […] When the physical pleasure aspect of sex is viewed as an enjoyed, but not essential, component of sex, couples no longer need to rely on perfect sexual functioning to engage in satisfying sex. Physical pleasure can come to be seen as “icing on the cake”, while relational intimacy is the cake itself.”
“Overall findings from neuroimaging studies of resilience suggest that the brains of resilient people are better equipped to tamp down negative emotion. […] In studies of rodents […] and primates […], early stress has consistently been associated with impaired brain development. Specifically, chronic stress has been found to damage neurons and inhibit neurogenesis in the hippocampus and medial prefrontal cortex […]. Stress has the opposite effect on the amygdala, causing dendritic growth accompanied by increased anxiety and aggression […]. Human studies yield results that are consistent with animal studies.”
I won’t cover the human studies in detail, but for example people have found when looking at the brains of children raised under bad conditions in orphanages in Eastern Europe and Asia that children who were adopted early in life (i.e., got away from the terrible conditions early on) had smaller amygdalae than children who were adopted later. They also note that smaller orbitofrontal volumes have been observed in physically abused children, with arguably(?) (I’m not sure about the validity of the instrument applied) a dose-response relationship between severity of abuse and the level of brain differences/changes observed, and smaller hippocampal volumes have been noted in depressed women with a history of childhood maltreatment (their brains were compared with the brains of depressed women without a history of childhood maltreatment).
“The positive associations between social support and physical health may be due in large part to the effect of positive relationships on cortisol levels […]. The presence of close, supportive relationships have been associated with lower cortisol levels in adolescents […], middle class mothers of 2-year old children […], elderly widowed adults […], men and women aged 47–59 […], healthy men […], college students […], 18–36 year olds from the UCLA community […], parents expecting their first child […], and relationship partners […] Overall, studies on relationship quality and cortisol levels suggest that close supportive relationships play an important role in boosting resilience.”
“Sharpe (2000) offered an insightful, developmental approach to understanding mutuality in romantic relationships. She described mutuality as a result of “merging” that consists of several steps, which occur and often overlap in the lifetime of a relationship. With the progression of the relationship, the partners start to recognize differences that exist between them and try to incorporate them into their existing concept of relationship. Additionally, both partners search for “his or her own comfort level and balance between time together and time apart” […]. As merging progresses, partners are able to cultivate their existing commonalities and differences, as well as develop multiple ways of staying connected. In truly mutual couples, both partners respect and validate each other’s views, work together to accomplish common goals, and resolve their differences through compromise. Moreover, a critical achievement of mutuality is the internalization of the loving relationship.”
I gave the book two stars on goodreads. The contributors to this volume are from Brazil, Spain, Mexico, Japan, Turkey, Denmark, and the Czech Republic; the editor is from Taiwan. In most chapters you can tell that the first language of these authors is not English; the language is occasionally quite bad, although you can usually tell what the authors are trying to say.
The book is open access and you can read it here. I have included some quotes from the book below:
“It is estimated that men and women with depression are 20.9 and 27 times, respectively, more likely to commit suicide than those without depression (Briley & Lépine, 2011).” [Well, that’s one way to communicate risk… See also this comment].
“depression is on average twice as common in women as in men (Bromet et al., 2011). […] sex differences have been observed in the prevalence of mental disorders as well as in responses to treatment […] When this [sexual] dimorphism is present [in rats, a common animal model], the drug effect is generally stronger in males than in females.”
“Several reports indicate that follicular stimulating and luteinizing hormones and estradiol oscillations are correlated with the onset or worsening of depression symptoms during early perimenopause […], when major depressive disorder incidence is 3-5 times higher than the male matched population of the same [age] […]. Several longitudinal studies that followed women across the menopausal transition indicate that the risk for significant depressive symptoms increases during the menopausal transition and then decreases in […] early postmenopause […] the impact of hormone oscillations during perimenopause transition may affect the serotonergic system function and increase vulnerability to develop depression.”
“The use of antidepressant drugs for treating patients with depression began in the late 1950s. Since then, many drugs with potential antidepressants have been made available and significant advances have been made in understanding their possible mechanisms of action […]. Only two classes of antidepressants were known until the 80’s: tricyclic antidepressants and monoamine oxidase inhibitors. Both, although effective, were nonspecific and caused numerous side effects […]. Over the past 20 years, new classes of antidepressants have been discovered: selective serotonin reuptake inhibitors, selective serotonin/norepinephrine reuptake inhibitors, serotonin reuptake inhibitors and alpha-2 antagonists, serotonin reuptake stimulants, selective norepinephrine reuptake inhibitors, selective dopamine reuptake inhibitors and alpha-2 adrenoceptor antagonists […] Neither the biological basis of depression […] nor the precise mechanism of antidepressant efficacy are completely understood […]. Indeed, antidepressants are widely prescribed for anxiety and disorders other than depression.”
“Taken together the TCAs and the MAO-Is can be considered to be non-selective or multidimensional drugs, comparable to a more or less rational polypharmacy at the receptor level. This is even when used as monotherapy in the acute therapy of major depression. The new generation of selective antidepressants (the selective serotonin reuptake inhibitors (SSRIs)), or the selective noradrenaline and serotonin reuptake inhibitors (SNRIs) have a selective mechanism of action, thus avoiding polypharmacy. However, the new generation antidepressants such as the SSRIs or SNRIs are less effective than the TCAs. […] The most selective second generation antidepressants have not proved in monotherapy to be more effective on the core symptoms of depression than the first generation TCAs or MAOIs. It is by their safety profiles, either in overdose or in terms of long term side effects, that the second generation antidepressants have outperformed the first generation.”
“Suicide is a serious global public health problem. Nearly 1 million individuals commit suicide every year. […] Suicide […] ranks among the top 10 causes of death in every country, and is one of the three leading causes of death in 15 to 35-year olds.”
“Considering patients that commit suicide, about half of them, at some point, had contact with psychiatric services, yet only a quarter had current or recent contact (Andersen et al., 2000; Lee et al., 2008). A study conducted by Gunnell & Frankel (1994) revealed that 20-25% of those committing suicide had contact with a health care professional in the week before death and 40% had such contact one month before death” (I’m assuming ‘things have changed’ during the last couple of decades, but it would be interesting to know how much they’ve changed).
“In cases of suicide by drug overdose, TCAs have the highest fatal toxicity, followed by serotonin and noradrenalin reuptake inhibitors (SNRIs), specific serotonergic antidepressants (NaSSA) and SSRIs […] SSRIs are considered to be less toxic than TCAs and MAOIs because they have an extended therapeutic window. The ingestion of up to 30 times its recommended daily dose produces little or no symptoms. The intake of 50 to 70 times the recommended daily dose can cause vomiting, mild depression of the CNS or tremors. Death rarely occurs, even at very high doses […] When we talk about suicide and suicide attempt with antidepressants overdose, we are referring mainly to women in their twenties – thirties who are suicide repeaters.”
“Physical pain is one of the most common somatic symptoms in patients that suffer depression and conversely, patients suffering from chronic pain of diverse origins are often depressed. […] While […] data strongly suggest that depression is linked to altered pain perception, pain management has received little attention to date in the field of psychiatric research […] The monoaminergic system influences both mood and pain […], and since many antidepressants modify properties of monoamines, these compounds may be effective in managing chronic pain of diverse origins in non-depressed patients and to alleviate pain in depressed patients. There are abundant evidences in support of the analgesic properties of tricyclic antidepressants (TCAs), particularly amitriptyline, and another TCA, duloxetine, has been approved as an analgesic for diabetic neuropathic pain. By contrast, there is only limited data regarding the analgesic properties of selective serotonin reuptake inhibitors (SSRIs) […]. In general, compounds with noradrenergic and serotonergic modes of action are more effective analgesics […], although the underlying mechanisms of action remain poorly understood […] While the utility of many antidepressant drugs in pain treatment is well established, it remains unclear whether antidepressants alleviate pain by acting on mood (emotional pain) or nociceptive transmission (sensorial pain). Indeed, in many cases, no correlation exists between the level of pain experienced by the patient and the effect of antidepressants on mood. […] Currently, TCAs (amitriptyline, nortriptiline, imipramine and clomipramine) are the most common antidepressants used in the treatment of neuropathic pain processes associated with diabetes, cancer, viral infections and nerve compression. […] TCAs appear to provide effective pain relief at lower doses than those required for their antidepressant effects, while medium to high doses of SNRIs are necessary to produce analgesia”. Do keep in mind here that in a neuropathy setting one should not expect to get anywhere near complete pain relief with these drugs – see also this post.
“Prevalence of a more or less severe depression is approximately double in patients with diabetes compared to a general population [for more on related topics, see incidentally this previous post of mine]. […] Diabetes as a primary disease is typically superimposed by depression as a reactive state. Depression is usually a result of exposure to psycho-social factors that are related to hardship caused by chronic disease. […] Several studies concerning comorbidity of type 1 diabetes and depression identified risk factors of depression development; chronic somatic comorbidity and polypharmacy, female gender, higher age, solitary life, lower than secondary education, lower financial status, cigarette smoking, obesity, diabetes complications and a higher glycosylated hemoglobin [Engum, 2005; Bell, 2005; Hermanns, 2005; Katon, 2004]”
Here are my first two posts about the book, which I have now finished. I gave the book three stars on goodreads, but I’m close to a four star rating and I may change my opinion later – overall it’s a pretty good book. I’ve read about many of the topics covered before but there was also quite a bit of new stuff along the way; as a whole the book spans very widely, but despite this the level of coverage of individual topics is not bad – I actually think the structure of the book makes it more useful as a reference tool than is McPhee et al. (…in terms of reference books which one might find the need to refer to in order to make sense of medical tests and test results, I should of course add that no book can beat Newman & Kohn). I have tried to take this into account along the way in terms of the way I’ve been reading the book, in the sense that I’ve tried to make frequent references in the margin to other relevant works going into more detail about specific topics whenever this seemed like it might be useful, and I think if one does something along those lines systematically a book like this one can become a really powerful tool – you get the short version with the most important information (…or at least what the authors considered to be the most important information) here almost regardless of what topic you’re interested in – I should note in this context that the book has only very limited coverage of mental health topics, so this is one area where you definitely need to go elsewhere for semi-detailed coverage – and if you need more detail than what’s provided in the coverage you’ll also know from your notes where to go next.
In my last post I talked a bit about which topics were covered in the various chapters in the book – I figured it might make sense here to list the remaining chapter titles in this post. After the (long) surgery chapter, the rest of the chapters deal with epidemiology (I thought this was a poor chapter and the authors definitely did not consider this topic to be particularly important; they spent only 12 pages on it), clinical chemistry (lab results, plasma proteins, topics like ‘what is hypo- and hypernatremia’, …), eponymous syndromes (a random collection of diseases, many of which are quite rare), radiology (MRI vs X-ray? When to use, or not use, contrast material? Etc.), ‘reference intervals etc.‘ (the ‘etc.’ part covered drug therapeutic ranges for some commonly used drugs, as well as some important drug interactions – note to self: The effects of antidiabetic drugs are increased by alcohol, beta-blockers, bezafibrate, and MAOIs, and are decreased by contraceptive steroids, corticosteroids, diazoxide, diuretics, and possibly also lithium), practical procedures (I was considering skipping this chapter because I’m never going to be asked to e.g. insert a chest drain and knowing how to do it seems to be of limited benefit to me, but I figured I might as well read it anyway; there were some details about what can go wrong in the context of specific procedures and what should be done when this happens, and this seemed like valuable information. Also, did you know that “There is no evidence that lying flat post procedure prevents headache” in the context of lumbar punctures? I didn’t, and a lot of doctors probably also don’t. You can actually go even further than that: “Despite years of anecdotal advice to the contrary, none of the following has ever been shown to be a risk factor [for post-LP headache]: position during or after the procedure; hydration status before, during, or after; amount of CSF removed; immediate activity or rest post-LP.”), and emergencies.
In this post I won’t cover specific chapters of the book in any detail, rather I’ll talk about a few specific topics and observations I could be bothered to write some stuff about here. Let’s start with some uplifting news about the topic of liver tumours: Most of these (~90%) are secondary (i.e. metastatic) tumours with an excellent prognosis (“Often <6 months”). No, wait just a minute… Nope, you definitely do not want cancer cells to migrate to your liver. Primary tumors, the most common cause of which is hepatitis B infection (…they say in that part of the coverage – but elsewhere in the book they observe that “alcohol is the prime cause of any liver disease”), also don’t have great outcomes, especially not if you don’t get a new liver: “Resecting solitary tumours <3cm across ↑3yr survival to 59% from 13%; but ~50% have recurrence by 3yrs. Liver transplant gives a 5yr survival rate of 70%.” It should be noted in a disease impact context that this type of cancer is far more common in areas of the world with poorly developed health care systems like Africa and China.
Alcoholism is another one of the causes of liver tumors. In the book they include the observation that the lifetime prevalence of alcoholism is around 10% for men and 4% for women, but such numbers are of course close to being completely meaningless almost regardless of where they’re coming from. Alcoholism is dangerous; in cases with established cirrhosis roughly half (52%) of people who do not stop drinking will be dead within 5 years, whereas this is also the case for 23% of the people who do stop drinking. Excessive alcohol consumption can cause alcoholic hepatitis; “[m]ild episodes hardly affect mortality” but in severe cases half will be dead in a month, and in general 40% of people admitted to the hospital for alcoholic hepatitis will be dead within one year of admission. Alcohol can cause portal hypertension (80% of cases are caused by cirrhosis in the UK), which may lead to the development of abnormal blood vessels e.g. in the oesophagus which will have a tendency to cause bleeding, which can be fatal. Roughly 30% of cirrhotics with varices bleed, and rebleeding is common: “After a 1st variceal bleed, 60% rebleed within 1yr” and “40% of rebleeders die of complications.” Alcoholism can kill you in a variety of different ways (acute poisonings and accidents should probably also be included here as well), and many don’t survive long enough to develop cancer.
As mentioned in the first post about the book acute kidney injury is common in a hospital setting. In the following I’ve added a few more observations about renal disease. “Renal pain is usually a dull ache, constant and in the loin.” But renal disease don’t always cause pain, and in general: “There is often a poor correlation between symptoms and severity of renal disease. Progression [in chronic disease] may be so insidious that patients attribute symptoms to age or a minor illnesses. […] Serious renal failure may cause no symptoms at all.” The authors note that odd chronic symptoms like fatigue should not be dismissed without considering a renal function test first. The book has a nice brief overview of the pathophysiology of diabetic nephropathy – this part is slightly technical, but I decided to include it here anyway before moving on to a different topic:
“Early on, glomerular and tubular hypertrophy occur, increasing GFR [glomerular filtration rate, an indicator variable used to assess kidney function] transiently, but ongoing damage from advanced glycosylation end-products (AGE—caused by non-enzymatic glycosylation of proteins from chronic hyperglycaemia) triggers more destructive disease. These AGE trigger an inflammatory response leading to deposition of type IV collagen and mesangial expansion, eventually leading to arterial hyalinization, thickening of the mesangium and glomerular basement membrane and nodular glomerulosclerosis (Kimmelstiel–Wilson lesions). Progression generally occurs in four stages:
1 GFR elevated: early in disease renal blood flow increases, increasing the GFR and leading to microalbuminuria. […]
2 Glomerular hyperfiltration: in the next 5–10yrs mesangial expansion gradually occurs and hyperfiltration at the glomerulus is seen without microalbuminuria.
3 Microalbuminuria: as soon as this is detected it indicates progression of disease, GFR may be raised or normal. This lasts another 5–10yrs.
4 Nephropathy: GFR begins to decline and proteinuria increases.
Patients with type 2 DM may present at the later stages having had undetected hyperglycaemia for many years before diagnosis.”
Vitamin B12 deficiency is quite common, the authors note that it occurs in up to 15% of older people. Severe B12 deficiency is not the sort of thing which will lead to you feeling ‘a bit under the weather’ – it can lead to permanent brain damage and damage to the spinal cord. “Vitamin B12 is found in meat, fish, and dairy products, but not in plants.” It’s important to note that “foods of non-animal origin contain no B12 unless fortified or contain bacteria.” The wiki article incidentally includes even higher prevalence estimates (“It is estimated to occur in about 6% of those under the age of 60 and 20% of those over the age of 60. Rates may be as high as 80% in parts of Africa and Asia.”) than the one included in the book – this vitamin deficiency is common, and if severe it can have devastating consequences.
On bleeding disorders: “After injury, 3 processes halt bleeding: vasoconstriction, gap-plugging by platelets, and the coagulation cascade […]. Disorders of haemostasis fall into these 3 groups. The pattern of bleeding is important — vascular and platelet disorders lead to prolonged bleeding from cuts, bleeding into the skin (eg easy bruising and purpura), and bleeding from mucous membranes (eg epistaxis [nose bleeds], bleeding from gums, menorrhagia). Coagulation disorders cause delayed bleeding into joints and muscle.” An important observation in the context of major bleeds is incidentally this: “Blood should only be given if strictly necessary and there is no alternative. Outcomes are often worse after a transfusion.” The book has some good chapters about the leukaemias, but they’re relatively rare diseases and some of them are depressing (e.g. acute myeloid leukaemia: according to the book coverage death occurs in ~2 months if untreated, and roughly four out of five treated patients are dead within 3 years) so I won’t talk a lot about them. One thing I found somewhat interesting about the blood disorders covered in the book is actually how rare they are, all things considered: “every day each of us makes 175 billion red cells, 70 billion granulocytes, and 175 billion platelets”. There are lots of opportunities for things to go wrong here…
Some ways to prevent traveller’s diarrhea: “If in doubt, boil all water. Chlorination is OK, but doesn’t kill amoebic cysts (get tablets from pharmacies). Filter water before purifying. Distinguish between simple gravity filters and water purifiers (which also attempt to sterilize chemically). […] avoid surface water and intermittent tap supplies. In Africa assume that all unbottled water is unsafe. With bottled water, ensure the rim is clean & dry. Avoid ice. […] Avoid salads and peel your own fruit. If you cannot wash your hands, discard the part of the food that you are holding […] Hot, well-cooked food is best (>70°C for 2min is no guarantee; many pathogens survive boiling for 5min, but few last 15min)”
An important observation related to this book’s coverage about how to control hospital acquired infection: “Cleaning hospitals: Routine cleaning is necessary to ensure that the hospital is visibly clean and free from dust and soiling. 90% of microorganisms are present within ‘visible dirt’, and the purpose of routine cleaning is to eliminate this dirt. Neither soap nor detergents have antimicrobial activity, and the cleaning process depends essentially on mechanical action.”
Falciparum malaria causes one million deaths/year, according to the book, and mortality is close to 100% in untreated severe malaria – treatment reduces this number to 15-20%. Malaria in returning travellers is not particularly common, but there are a couple thousand cases in the UK each year. Malaria prophylaxis does not give full protection, and “[t]here is no good protection for parts of SE Asia.” Multidrug resistance is common.