Abstain from Alcohol to Decrease Risk of Atrial Fibrillation

Here is a press release about a study that was presented by has not yet been published. Perhaps the best study design for evaluating the benefits/harms of alcohol.

Lead Exposure in Childhood can lead to Personality Changes

Here is the link to a simplified version

Readmissions and Mortality–Any Difference by Race?

Since the introduction of Hospital Readmission Reduction Program by the CMS, there has been a significant decrease in readmissions for all targetted diseases. However, studies have raised concern that although readmissions are decreasing, there may be an increase in mortality.

A recent study showed that there is no difference in mortality between white and black patients. Authors used interrupted time-series analysis. I enjoyed statistical modelling but wonder if the within-hospital and between hosptial effects were properly accounted for. In other words, the assumption in their modeling is that both effects are the same (unlikely to be true). It is possible that the within and between effects are different and may shed a better light on what is happening at individual hospital level and what is happening across hospitals. Having said that, it is an interesting study with important implications.

Are Machine Learning Tools Better than Standard Tools in Predicting Readmissions

Just saw this study where authors compared standard readmission tools (HOSPITAL score, modified LACE score, and Maxim/RightCare score) with a model developed using machine learning. Authors found that machine learning score (they called it Baltimore Score or B-score) performed much better than standard tools.

While I agree that machine learning tools will likely outperform standard methods. Standard methods are quite a bit of oversimplification of the real life, machine learning tools less so. However, I doubt that authors have got their model right. Two reasons: One, their sample size is relatively small. Two, they have not validated their tool in a new dataset.

Social risk factors adjustment for readmission penalties

I have shown, in my previous work, that social risk factors affect hospital performance. CMS, at th eurging of Congress, will be including including social risk factors in their patient risk models. Here is an interesting paper that examined retrospectively the effect of adjustment for social risk factors on readmission penalties and found that the penalties will drop by almost half for safety-net hospitals. I am certain that these adjustment will bring more fairness in hospital comparisons and will decrease the amount of penalty these safety-net hospitals have to face. 

Obesity and Hospital Readmissions

The link between obesity and readmissions is not as clear cut, despite the fact that almost 40% of older adults in the US are obese. In this relatively large study examining the readmission rates of obese nursinghome patients, authors found that the relationship is perhaps complex and islikely affected by age and co-morbid conditions.

Rebate on Prescription Drugs

Illuminating article; must read. Here are two sentences that capture the essence of this issue: “In 2016, leading products in these classes had total pre-rebate spending in Part D of $2.5 billion (Lantus Solostar) and $4.4 billion (Harvoni). For an individual patient, this would reduce list prices on which their deductibles and co-insurance are calculated from $417 to $142 for patients filling a 1-month supply for Lantus Solostar and from $92 648 to $35 206 for patients filling an 84-day course of treatment with Harvoni, assuming class-level rebates applied to these products.”

Failure of Patient-centerd Transitions of Care Program to Improve Outcomes in Heart Failure Patients

Improving patient care through focus on transitions of care is hard! There are very few studies that have evaluated strategies that work in a randomized controlled trial (RCT) fashion and none has been able to show any benefit. Here is a large RCT that failed to show a benefit.

What is that works? And works consistently?

Number Needed to Treat

Number needed to treat is an important concept as it simplifies the communication of the effect size from clinical studies. It tells us the number of patients needed to be treated to get the desired outcomes (or an undesireable adverse event). Here is a much longer description from JAMA.

Physician Organizations’ contribution to political Candidates and NRA ratings

Must read article in JAMA. Here is a graph that says is all; full article is here.

Quick Overview of Mediation Analysis

JAMA recently published this overview of Mediation Analysis; often a misunderstood statistical method (and some may argue a method for causal modeling), mediation analysis is a powerful technique that can help to delineate biological or psychological mechanisms.

Physicians Support Tighter FDA Control on New Drug Approval

An interesting research letter published in JAMA Internal Medicine reports that 80% of physicians agree with the strict FDA approval process to protect public from ineffective or dangerous drugs. Further, 60% thought that FDA should not allow off-label promotion of drugs to physicians.

Genistein, a Phytoestrogen, and Mortality

Several studies in medical literature and countless lay-media articles promote the benefits of phytoestrogens. In this large study, using data from NHANES, Marcelo and colleagues showed that that high levels of genistein in urine are associated with lower mortality. In particular, it decreases mortality from all causes.

Apixaban in ESRD and Atrial Fibrillation

Patients with ESRD (end-stage renal disease) are usually prescribed coumadin when they need anticoagulation; the reason being that we know very little (or not at all) about the effect of new oral anticoagulants in patients with ESRD.

In this study, Siontis et al performed a retrospective cohort study of Medicare beneficiaries with ESRD and atrial fibrillation, the later an indication for anticoagulation. Outcomes were compared between patients who were treated with apixaban versus patients who were treated with warfarin. Authors examined the survival difference between the two groups for stroke or systemic embolism, major bleeding, gastrointestinal bleeding, intracranial bleeding, and death using Kaplan–Meier analyses and hazard ratios (HRs) and 95% CIs were obtained using Cox regression analyses.

Authors found that there was no difference in stroke and systemic embolism between the two groups. However, the group taking apixaban had 28% lower risk of major bleed.

While this is retrospective data, and clinical trial data is lacking, this study will support the use of new oral anticoagulants in ESRD patients.

Is Science Getting Less Bang for its Buck?

Here is an interesting article published in The Atlantic which claims that the productivity in science is declining. The investment in science is increasing but the pace of novel or truly important discoveries is decreasing. They give various reasons; I have few additional thoughts that I assume authors thought of but were not included in this piece.

1. The age of scientist at discovery is increasing due to the large volume of knowledge we ‘force’ young scientist to learn. We have formalized ‘learning’ to an extent that we feel it is obligatory for anyone to ‘know’ it all before moving forward. Just as an example, the ‘required’ courses to take are often not directly relevant to the learner’s interest or the to the topic. WE have added those without any scientific evidence that such additional courses help with discovery. We preach evidence, we prefer not to teach by science. And when we try to accumulate evidence, we do it using irrelevant outcomes. This is the problem with education in general and not with science education.

2. Truly novel discoveries happen in spurts. Discovery of zero was truly important, one may argue more important than general relativity. Perhaps discovery of algebra and calculus were also more important, and fundamental, than general relativity. But these discoveries are not ‘novel’ anymore for us. I believe new discoveries happen after we have utilized the older discoveries to close to the fullest extent. Imagine a new discovery as a new house; once we build a new house, we start filling it, decorating it, accumulating useful (and some junk) ‘stuff’. This is perhaps what happens with truly important discoveries. A truly important discovery is followed by many small discoveries over next many years until the potential of new discovery has been fully realized and then another new discovery happens.

Serum creatinine in critically ill patient

An interesting, short and sweet article in JAMA highlighting that serum creatinine increase in critically-ill patients may underestimate the degree of AKI.

They give following reasons for this underestimation:
1. Creatinine production decreases in sepsis, hence there is decreased release of creatinine and slow rise in serum creatinine
2. Critically-ill patients receive large-volume resuscitation and hence dilute serum creatinine. Of note, the volume of distribution of creatinine is about 65% of body weight.

Having said that, there does not appear to be any good alternatives for determining renal function ad GFR estimation in such population.

Vitamin D and Cardiorespiratory Fitness

Here is a study just published showing relationship between cardiorespiratory fitness and vitamin D levels. The study adjusted for various confounders and the relationship was independent of these confounders. The study is cross-sectional and hence the direction of causal effect is difficult to determine. That is, whether greater cardiorespiratory fitness is associated with more time spent outside and hence more sunlight exposure and vitamin D formation or whether vitamin D, through its effects on muscles, nerves, bones, results in higher cardiorespiratory fitness

Deep Learning in Pathology

Here is an intersting article, showing the role of AI in pathological diagnoses. Medical speciliaties most dependent on pattern recognition, such a pathology, dermatology, or radiology, are more likely to get AI assistance sooner. With time, it is quite possible that AI can replace such physicians. For now, it appears that AI will help them work faster. Remember, increasing efficiency means need for fewer physicians in such specilaties and possibly decliing salary.

Incentives and Work

An interesting article which is also very germane to academic physicians. In particular the sentence “what drives most academics to the university on a given day (including evenings and weekends) is not the money (otherwise we would work in the private sector) or the stability of the income stream (because the probability of losing a job is close to zero for a tenured academic). In fact, Stern (2004) shows that “scientists pay to be scientists.”  is right on the spot. One can say about physicians in academia that they “pay to be in academics”. In almost every case, they can earn quite a bit more in private practice. It is the meaning in their work that motivates them.

Aspirin and Body Weight

Low dose aspirin has been shown to reduce cardiovascular events but the observed effect may vary by weight. In fact, in one of our studies, we have shown that not only obese individuals had greater baseline platelet reactivity, they also had greater residual platelet reactivity after low-dose aspirin therapy. Comparing obese and nonobese individuals after aspirin therapy, results for aggregometry to collagen were 6.7 vs 6.1 ohms, P=.008; aggregometry to adenosine diphosphate were 13.1 vs 11.8 ohms,P<.0001; aggregometry to arachidonic acid (AA) were 4.9% vs 8.3% nonzero aggregation, P=.002; urinary excretion of 11-dehydro-thromboxane B2 (Tx-M) were 4.9% vs 8.3% nonzero aggregation, P=.002; and aspirin resistance were 26.% vs 20.5%, P=.002; respectively.

Now an individual-patient meta-analysis of primary prevention randomized controlled trials with low-dose aspirin have shown that clinical outcomes are also different in patients with weight>70Kg than in patients with weight<70Kg. On the other hand, when a higher dose of aspirin was examined, individuals with weight>70Kg obtained clinical benefits. Clinical benefits were not limited to cardiovascular outcomes but also included colorectal outcomes.

An obvious implication of such studies is that individuals with weight>70Kg should take perhaps more than one baby aspirin to receive benefit from aspirin.