Aug 28, 2020 This Week in Cardiology Podcast

John M. Mandrola, MD


August 28, 2020

Please note that the text below is not a full transcript and has not been copyedited. For more insight and commentary on these stories, subscribe to the This Week in Cardiology podcast.

In This Week’s Podcast

For the week ending August 28, 2020, John Mandrola, MD comments on the following news and features stories.

Explainer on Cardiac Effects in COVID

I cannot believe it but we have to talk again about the controversial JAMA-Cardiology cardiac MRI after COVID study. My friend Anish Koka, a cardiologist in Philadelphia, has authored an excellent piece on the dubious science surrounding the cardiac effects of coronavirus. Dr. Koka’s stimulus for writing such a nice explainer is that US college football programs and the NCAA have cited dubious scientific reasons for cancelling their season, including the cardiac MRI study.

The important issues for cardiologists and really all medical people are a) the specifics of the matter of cardiac involvement with this virus, b) the critical appraisal of science, and c) the utter necessity of accurate science communication in the public.

Nearly immediately after publication of the JAMA-Cardiology paper, Darrel Francis and Graham Cole from Imperial College, among a handful of others, noted that the numbers in the main table were mathematically impossible. An example was something as simple as the IQR (interquartile range) surrounding age. They were simply too narrow to be true.

These revelations led to a rapid review of the paper and this week, JAMA-Cardiology published a revised paper and letter of explanation from the authors. These documents say the main findings are upheld. But I don’t think that is true.

Back to Darrel Francis’s Twitter time line. Here he shows the before and after. The short story is that, yes, the numbers were corrected, the IQRs changed to something else, but something happened to the main finding of the paper—the T1 abnormalities.

Here the number of normal controls with abnormal findings doubled, the number of risk factor (RF) control people went from 23 to 33. The authors ran a p-value on the three columns (recovered COVID, normal, and RF controls). It was significant. But this is totally wrong. COVID patients are mostly middle-aged or older. You have to compare the post infection MRI to those matched on risk factors. If you do that: 73% of 100 COVID patients had the abnormal T1, 58% of 57 non-COVID patients (with similar risk factors) had it. Francis calculated this p-value and it is no longer significant (though close)

In summary: A major journal publishes a small non-randomized study of cardiac MRI after a viral infection. No one really knows what a cardiac MRI would like after severe viral infection from say parainfluenza, human metapneumovirus, or influenza. The original paper gets more than a half a million views. Media goes ballistic over it. But nearly all the data in the main table is wrong. Mathematically impossible. I did not see the obvious irregularities; the peer-reviewers did not; the editors did not.

Convalescent Plasma: Why We Need RCTs

Last weekend, Dr. Steve Hahn, the FDA commissioner, gave a news conference in which he presented the results of an observational non-randomized study from the Mayo group. Note the study was from a preprint, no peer review.

Convalescent plasma was donated by recently-recovered COVID-19 survivors, and the antibody levels in the units collected were unknown at the time of transfusion. A gradient of mortality was seen in relation to antibody levels in the transfused plasma. High IgG did better than medium IgG and low IgG

The pooled relative risk of mortality among patients transfused with high antibody level plasma units was 0.65 [0.47-0.92] for 7 days and 0.77 [0.63-0.94] for 30 days compared to low antibody level plasma units. But Hahn mixed up relative and absolute risk reduction. He turned the HR of .65 into a 35% absolute risk reduction. He said convalescent plasma would save 35 out of 100 people given the agent. He corrected the error later in the week.

But the real tragedy of convalescent plasma is that tens of thousands of people have received it and we have no idea if it works because, in a disease that most people recover from, we can’t know if something works without an adequate control and a proper blinded trial. Look at remdesivir. One study made it look good, others not so much. And we still haven’t heard the longer-term follow-up on the positive remdesivir study.

PCI in the VA vs the Community

JACC published a provocative observational study comparing outcomes after percutaneous coronary intervention (PCI) for stable coronary artery disease in the VA system vs community hospitals. This is an important question because the VA system is essentially a single-payer National Health Service-like system embedded within the US system. Many Americans falsely believe such a system is inherently inferior; there is a general feeling among some that private systems provide better care.

The study involved about 9000 patients, two-thirds of whom had PCI in the VA and one-third out in community facilities. Patients treated in the community had a 33% higher death rate. There was early separation of the curves, which could suggest differences in safety of the procedure, or could indicate that sicker patients underwent procedures in the community.

The question in non-random comparisons like this is the potential for confounding. The authors used a hypothetical model to estimate the size of the baseline differences that could account for the sizable difference in mortality. They suggest that if a confounder was present—eg, the sicker patients went to the community—it would have to be a big difference, and this is unlikely.

In addition to the non-randomized comparison and likely confounding, the authors tell us they used actual medical records for documenting outcomes in the VA but used administrative databases for the community hospital group. I am surprised that JACC did not force the authors to expand on this hypothetical model of estimating confounding. I am not a stats person, but it seems we ought to have more weight given to adjustments for baseline differences.

ESC Preview

The European Society for Cardiology meeting, like all other medical meetings, has moved online. But we will still learn the results of important trials. The lead study is EMPOROR-REDUCED which is the second RCT of a SGLT2 inhibitor for patients with heart failure with reduced ejection fraction (HFrEF). We know from a press release that the empagliflozin vs placebo trial met its primary endpoint of cardiovascular death and heart failure hospitalization. We don’t know by how much. The magnitude of benefit is important because dapagliflozin looked quite impressive in the DAPA-HF trial. Speaking of SGLT2 inhibitors and the DAPA-HF, ESC will feature a DAPA-CKD trial (n ≈ 4000), which will test whether dapagliflozin preserves kidney function in patients with chronic kidney disease . I know this is a kidney outcomes trial, but if positive by a lot, then the drug class gets even more momentum.

Another big study is the EAST trial. This is a pragmatic, multicenter RCT studying the effect of early rhythm control vs usual care in patients with atrial fibrillation. Rhythm control in EAST could be with either an antiarrhythmic drug or ablation.

The seminal AFFIRM trial clearly showed that rhythm control in older patients offered no benefits over rate control in older patients who were minimally symptomatic. But rhythm control deserves more respect than it gets. While sinus rhythm is preferred, getting there can be hazardous. Drug side effects and procedural complications are no small thing.


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