Circulation March 30, 2021 Issue Circulation on the Run

For this week's Feature Discussion, please join authors Michael Ackerman, Christopher Haggerty, editorialist Michael Rosenberg, and Associate Editor Nicholas Mills as they discuss the original research articles “Artificial Intelligence-Enabled Assessment of the Heart Rate Corrected QT Interval Using a Mobile Electrocardiogram Device,” “ Deep Neural Networks Can Predict New-Onset Atrial Fibrillation From the 12-Lead Electrocardiogram and Help Identify Those at Risk of AF-Related Stroke,” and “Trusting Magic: Interpretability of Predictions from Machine Learning Algorithms.”
 
TRANSCRIPT BELOW:
Dr. Carolyn Lam:
Welcome to Circulation on the Run, your weekly podcast summary and backstage pass to the journal and its editors. We're your cohosts. I'm doctor Carolyn Lam, associate editor from the National Heart Center and Duke National University of Singapore.
Dr. Greg Hundley:
And I'm Greg Hundley, associate editor, director of the Pauley Heart Center at VCU Health in Richmond, Virginia. Well Carolyn, this week's feature, it's kind of a new thing for us. It's more than our double feature; it's actually a forum, where we're going to have two papers discussed, we'll have both authors represented from each of those two papers, we'll have an editorialist, and we'll have one of our associate editors. And the topic, Carolyn, just to keep you in suspense, is really on machine learning and actually how that can be applied to 12 lead electrocardiograms. But before we get to that, how about we grab a cup of coffee and start off on some of the other articles in this issue? Would you like to go first?
Dr. Carolyn Lam:
Yes, I would, but you're really keeping me in suspense. But first, let's focus on health related quality of life. We know that poor quality of life is common in heart failure, but there are few data on heart health related quality of life and its association with mortality outside of the Western countries. Well, until today's paper. And it's from the Global Congestive Heart Failure, or GCHF study, the largest study that has systematically examined health-related quality of life as measured by the Kansas City cardiomyopathy questionnaire 12, or KCCQ, and its association with outcomes in more than 23,000 patients with heart failure across 40 countries, in eight major geographic regions, spanning five continents.
Dr. Greg Hundley:
Wow, Carolyn. That KCCQ 12, that has been such an interesting tool for us to use in patients with heart failure. So what did they find in this study?
Dr. Carolyn Lam:
Really important. So the health-related quality of life differs considerably between geographic regions with markedly lower quality of life related to heart failure in Africa than elsewhere. Quality of life was a strong predictor of death and heart failure hospitalization in all regions, irrespective of symptoms class, and in both preserved and reduced ejection fraction. So there are some important clinical implications, namely that health-related quality of life is an inexpensive and simple prognostic marker that may be useful in characterizing symptom severity and prognosis in patients with heart failure. And there is certainly a need to address disparities that impact quality of life in patients with heart failure in different regions of the world.
Dr. Greg Hundley:
Very nice, Carolyn. Well, I'm going to turn to the world of basic science and bring us a paper from David Merryman from Vanderbilt University. So Carolyn, myocardial infarction induces an intense injury response, which ultimately generates a collagen dominated scar. Cardiac myofibroblasts are the cells tasked with depositing and remodeling collagen and are a prime target to limit the fibrotic process post myocardial infarction. Now Carolyn, serotonin 2B receptor signaling has been shown to be harmful in a variety of cardiopulmonary pathologies, and could play an important role in mediating scar formation after MI. So Carolyn, these investigators emp