Maintaining Competency and Physician Responsibility

Santen et al wrote a viewpoint in JAMA and propose the following 5 considerations to address competency decline with age and with introduction of new technology and/or procedures.

1. Lifelong learning and mechanisms to ensure maintenance of certification.
2. Responsibility to keep training.
3. Choosing practices that involve less exposure to procedures or content for which physicians are no longer expert
4. Self-assessment and reflection.
5. Responsibility of the health care system to ensure competency of physicians and surgeons for performing procedures.

These proposals are common sense or a no-brainer. However, the devil is always in the details. For example, how to assess lifelong learning? What is the evidence behind certain methods of lifelong learning? Is it possible that the physicians who self-reflect and self-assess are the ones who need it the least? If so, how to encourage physicians to self-reflect? One can go on and on but I hope I made the point. But I want to make a larger point. Medical education obsessively teaches evidence-based medicine, however, very few, if any, medical education methods have even a weak evidence to support them (as long as we do not include expert advice into evidence). It will be rare to see any medical education methodology that has been rigorously studied like we study medical interventions. No wonder we have increasing burnout among medical students, residents, and physicians; it is time we face the fact that our prescriptions for teaching medicine lack scientific evidence.

Fragility Index for Randomized Controlled Trials

An interesting question – how ‘fragile’ are the results of a randomized controlled trial (RCT)?

RCTs are gold-standard for determining the efficacy of a treatment. RCTs randomly assigned patients to an intervention arm or to a placebo (or standard of care or active treatment) arm. Because patients are randomly assigned, we expect that all patient characteristics (genetic, environmental etc.) would be balanced in the two groups. RCTs are often published with significant results – small RCTs without significant results are generally either not published or published in low-tier journals and don’t get prominence

Even when we randomly assign patients to a treatment arm or control arm, there is always a possibility that the two arm may be imbalanced by chance on measured or unmeasured variables. Further, it is also possible that just by chance one group may have statistically significant result than the other group without any true benefit (or harm) of the treatment. While we generally use a p-value of less than 0.05 (which says that there is a 1 in 20 probability that the results are observed due to chance only – not the right definition but its simple!), there remains a small chance that results will be not significant.

In comes ‘Fragility Index’, a measure of determining the robustness of results. Fragility index is the minimum number of patients who must be moved from the nonevent group to the event group to turn a significant result nonsignificant. The fragility index is an easy to calculate index that provides an intuitive way to understand the precision of trial results. Knowing the fragility index and comparing it to the number of patients lost to follow-up can help to understand the uncertainty in evidence even when a study has positive results.

Khan et al, examined cardiovascular clinical trials published between 2007-17 in major Cardiology journals. All trials were large with >500 patient enrollment. Among the 123 RCTs the median fragility index was 13.In almost 1/3rd of trials, the number of patients lost to follow-up was more than the fragility index.

In another study Gaudino et al examined the clinical trials used to support evidence in cardiology guidelines and determined the fragility index. They found that more than a quarter of RCTs supporting current guidelines on myocardial revascularization have a fragility index 3 or lower. Further over 40% of trials had a fragility index which was lower than the number of patients lost to follow-up.

Vaso-Occlusive Crisis in Sickle Cell Patients

Hemoglobin S (HbS) is an abnormal form of hemoglobin and is transmitted through genetically from parents to a child. Normal hemoglobin is mostly made up of 4 globin chains; 2 alpha chains and 2 beta chains. The underlying problem is a single mutation in the beta-chain of the hemoglobin where adenine nucleotide is replaced with a thymidine nucleotide resulting in a missense mutation and changing the amino acid glutamate at no. 6 position with valine. This change in amino acids from glutamate to valine results in changes in the 3-dimensional structure of the beta-chain of hemoglobin. These changes include 1) lower affinity for oxygen, 2) ability to join with other hemoglobin molecules and form polymers, 3) increase oxidation of the RBC cell membrane proteins.

Normal hemoglobin gets oxygenated in the lungs and carries oxygen to the tissues. Oxygen is released in the tissues and hemoglobin gets deoxygenated and returns back to the lungs for oxygenation. Normal hemoglobin remains soluble within the RBC throughout this process. On the other hand, deoxygenated HbS starts forming long filamentous through polymerization of hemoglobin molecules. Importantly, the process takes several seconds in fresh red blood cells (RBC) before polymerizations occurs and there is sufficient time for RBCs to return back to the lungs and get oxygenated.

However, some cells continue to get stuck in blood vessels resulting in completion of polymerization and breakdown of RBCs within the vessels (called intravascular hemolysis). This chronic, slow process of premature destruction of RBC in sickle cell patients is the reason for chronic anemia as well as other slowly developing manifestations of sickle cell disease.

In sickle cell vaso-occlusive crisis, large number of blood vessels are blocked resulting in marked pain and morbidity. Typically, the crisis is precipitated by some event, such as dehydration or an infection. The event stimulates the vascular endothelium making them sticky through expression of cell-binding receptors on the surface. These receptors then bind with other receptors on the surface of RBCs, white blood cells, and platelets resulting in blockage of the vessel lumen. The red blood cells with HbS are already primed to binding with other cells through expression of certain proteins as well as exposure of certain lipid products on the surface. Thus, the vaso-occlusive crisis results from the interaction of HbS containing RBC, endothelium, white blood cells, and platelets.

Physician Burnout & Patient Satisfaction/Experience

There have been concerns that physician burnout leads to lower patient satisfaction. In fact, some studies have found that patient satisfaction is lower among physicians with higher levels of burnout. A meta-analysis published in 2018 assimilated data and reached to the same conclusion. However, the quality of data, and studies, is questionable and there is a need for better conducted studies to examine this relationship.

A recently published article, by Howell et al., in the Journal of Patient Experience found no relationship between patient satisfaction and physician burnout domains of exhaustion and disengagement. This is an interesting finding and has strong implications. What it shows is that despite having high levels of burnout, physicians are able to function in a way that their patients don’t see a difference based on their burnout level. The brunt of burnout is faced by physicians and they shield their patients from its effects, likely at high personal cost.

Obviously, there may be other explanations – for example, the tools used to measure physician burnout are not reliably measuring burnout or that the tools to measure patient satisfaction with physicians are inaccurate and have large measurement bias. Both of these two explanations are possible but less plausible.

AI in Health Care–National Academy of Medicine’s Perspective

Here is the full report

Here are some highlights:

1. Promoting population-representative data with accessibility, standardization, and quality is imperative
2. Prioritize ethical, equitable, and inclusive health care AI while addressing explicit and implicit bias
3. Contextualizing the dialogue of transparency and trust requires accepting differential needs.
4. Near-term focus is needed on augmented intelligence vs AI autonomous agents
5. Develop and deploy appropriate training and educational programs to support health care AI.
6. Leverage frameworks and best practices for learning health care systems, human factors, and implementation science to address the challenges in operationalizing health care AI
7. Balance innovation with safety via regulation and legislation to promote trust.

Vasodilatation in Acute Heart Failure

Acute heart failure is a condition when the cardiac output (the amount of blood pumped by heart every minutes) is not sufficient to meet the needs of the body. Cardiac output depends on how much blood is in the heart before it starts contracting (cardiac pre-load), how strongly hear contracts (cardiac contractility), how much resistance heart faces when pumping blood into the arteries (cardiac after-load, or peripheral vasoconstriction), and how many times heart beats in a minutes.

For a failing heart, increasing the force of contraction and decreasing the pressure against which it pumps blood (after-load or vasoconstriction) are important factors. In fact, peripheral vasodilators such as ACE inhibitors or ARB are standards of care for heart failure patients. One may ask, what if we decrease the pressure against which heart pumps blood really low, in other words, if we cause high (intensive) vasodilation with drugs. This particular hypothesis was tested in The GALACTIC Study recently published in JAMA.

Interestingly, authors found no benefit of intensive vasodilatation on composite endpoint of death or rehospitalization. Further, the intensive vasodilation arm had higher risk of adverse effects such as worsening renal function, hypokalemia, dizziness, and hypotension.

The results are important because they suggest that while we focus on cardiac output, blood flow to individual organ (or fraction of cardiac output received by various organs may be as important, if not more important. Intensive vasodilatation likely results in poor perfusion to various organ resulting in increased adverse effects.

Sleepiness after work, Burnout, and Empathy

Tiredness after work, particularly shift work is common. How this relates to burnout and empathy is poorly explored. This study assessed the effects of shift (Day, Night), time of day (AM, PM), and gender (Male, Female) on sleepiness, empathy, and burnout in medical students. Working a 12 h night shift resulted in increased sleepiness as compared to a 12 h day shift. Sleepiness after a night shift resulted in differences in empathy. The sleepier the participant after working the 12 h shift, the lower their emotional empathy score.Similarly, sleepiness was associated with higher levels of burnout and females were affected more than men.