OCT 24, 2022 6:00 AM PDT

Can Smartwatch Apps Overcome Limitations to Detect Atrial Fibrillation?

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In a recent study published in the Canadian Journal of Cardiology, an international team of researchers led by Laval University in Canada examine the accuracy of electrocardiography (ECG) with the Apple Watch that could be used to detect atrial fibrillation (AF). This study holds the potential to help us better understand the benefits and drawbacks of using smartwatches for health purposes.

"Earlier studies have validated the accuracy of the Apple Watch for the diagnosis of AF in a limited number of patients with similar clinical profiles," said Dr. Marc Strik, MD, PhD, of the LIRYC institute, Bordeaux University Hospital in France, and a co-author on the study. "We tested the accuracy of the Apple Watch ECG app to detect AF in patients with a variety of coexisting ECG abnormalities."

Of the 734 patients involved in the study, about 20% experienced a failure in their smartwatch ECG to process an automatic diagnosis. It was also found that the risk of detecting a false positive automated AF was greater for patients with premature atrial or ventricular contractions (PACs/PVCs), second- or third-degree atrioventricular-block, or sinus node dysfunction.

"These observations are not surprising, as smartwatch automated detection algorithms are based solely on cycle variability," noted Dr. Strik, who explained that PVCs cause short and long cycles, which increase cycle variability. "Ideally, an algorithm would better discriminate between PVCs and AF. Any algorithm limited to the analysis of cycle variability will have poor accuracy in detecting AT/AFL. Machine learning approaches may increase smartwatch AF detection accuracy in these patients."

Several experts in the field observed in a follow-up editorial that this study is the first “real-world” study to examine how the Apple Watch can be used as a diagnostic tool for AF.

"It is of remarkable importance because it allowed us to learn the performance of the Apple Watch in the diagnosis of AF is significantly affected by the presence of underlying ECG abnormalities. In a certain manner, the smartwatch algorithms for the detection of AF in patients with cardiovascular conditions are not yet smart enough. But they may soon be," said Dr. Andrés F. Miranda-Arboleda and Dr. Adrian Baranchuk in the editorial.

"With the growing use of smartwatches in medicine, it is important to know which medical conditions and ECG abnormalities could impact and alter the detection of AF by the smartwatch in order to optimize the care of our patients," said Dr Strik. "Smartwatch detection of AF has great potential, but it is more challenging in patients with pre-existing cardiac disease."

Sources: Canadian Journal of Cardiology

As always, keep doing science & keep looking up!

About the Author
Master's (MA/MS/Other)
Laurence Tognetti is a six-year USAF Veteran who earned both a BSc and MSc from the School of Earth and Space Exploration at Arizona State University. Laurence is extremely passionate about outer space and science communication, and is the author of “Outer Solar System Moons: Your Personal 3D Journey”.
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