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JAMA Clinical Reviews

Interviews about ideas & innovations in medicine, science & clinical practice. Listen & earn CME credit
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Now displaying: February, 2019

In-depth interviews about current ideas and innovation in medicine, science, and clinical practice.

Feb 26, 2019

Great controversy exists regarding the safety of surgery when the attending surgeon allows someone else to perform parts of the operation. These practices are necessary components of surgical training, but how safe this is for patients remains unknown. In this podcast we discuss the risks and benefits associated with overlapping and concurrent surgery with a recognized expert in this topic, Michelle M. Mello, JD, PhD, a professor of law at Stanford University and the Department of Health Research and Policy, Stanford University School of Medicine, California.

Feb 26, 2019

COPD is common enough that it is responsible for 3% of all clinic visits in the United States. Clinicians will undoubtedly deal with this disease in their practice. How to diagnose and manage it is reviewed by Frank C. Sciurba, MD, a professor of medicine from the University of Pittsburgh, Pennsylvania.

Feb 14, 2019

Next-generation sequencing is a catchall term for new, high-throughput technologies that allow rapid sequencing of a full genome. It can be used to sequence a patient’s DNA in diagnosing a genetic disorder or characterizing a cancer, but can also be used to sequence the genome of a pathogenic bacteria, virus, fungi, or parasites. In this JAMA clinical review podcast, we talk with authors Marta Gwinn, MD, MPH, and Gregory L. Armstrong, MD, from the CDC, about how next-generation sequencing of infectious pathogens is being implemented in clinical practice and in public health surveillance for infectious disease.

Feb 12, 2019

E-values are a new tool that enables investigators to estimate the likelihood that some unmeasured confounder might overcome seemingly positive results. They are very easy to calculate and any reader of the medical literature can do this calculation to get a sense for how likely it is that there is some unmeasured factor in an observational study that might negate otherwise seemingly positive findings.

Read the article: Using the E-Value to Assess the Potential Effect of Unmeasured Confounding in Observational Studies

E-Value Calculator

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