Are smartwatch health apps to detect atrial fibrillation smart enough?
Philadelphia | October 12, 2022
Mobile health technology to detect atrial fibrillation generates a high rate of false positives and inconclusive results in some patients with certain cardiac conditions, investigators report in the Canadian Journal of Cardiology
Extended cardiac monitoring in patients and the use of implantable cardiovascular electronic devices can increase detection of atrial fibrillation (AF), but the devices have limitations including short battery life and lack of immediate feedback. Can new smartphone tools that can record an electrocardiogram (ECG) strip and make an automated diagnosis overcome these limitations and facilitate timely diagnosis? The largest study(opens in new tab/window) to date, in the Canadian Journal of Cardiology(opens in new tab/window), published by Elsevier, finds that the use of these devices is challenging in patients with abnormal ECGs. Better algorithms and machine learning may help these tools provide more accurate diagnoses, investigators say.
“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,” explained lead investigator Marc Strik, MD, PhD, LIRYC institute, Bordeaux University Hospital, Bordeaux, France. “We tested the accuracy of the Apple Watch ECG app to detect AF in patients with a variety of coexisting ECG abnormalities.”
The study included 734 consecutive hospitalized patients. Each patient underwent a 12-lead ECG, immediately followed by a 30-second Apple Watch recording. The smartwatch’s automated single-lead ECG AF detections were classified as “no signs of atrial fibrillation,” “atrial fibrillation,” or “inconclusive reading.” Smartwatch recordings were given to an electrophysiologist who conducted a blinded interpretation, assigning each tracing a diagnosis of “AF,” “absence of AF,” or “diagnosis unclear.” A second blinded electrophysiologist interpreted 100 randomly selected traces to determine the extent to which the observers agreed.
In approximately one in every five patients, the smartwatch ECG failed to produce an automatic diagnosis. The risk of having a false positive automated AF detection was higher for patients with premature atrial and ventricular contractions (PACs/PVCs), sinus node dysfunction, and second- or third-degree atrioventricular-block. For patients in AF, the risk of having a false negative tracing (missed AF) was higher for patients with ventricular conduction abnormalities (interventricular conduction delay) or rhythms controlled by an implanted pacemaker.
The cardiac electrophysiologists had a high level of agreement for differentiation between AF and non-AF. The smartphone app correctly identified 78% of the patients who were in AF and 81% who were not in AF. The electrophysiologists identified 97% of the patients who were in AF and 89% who were not.
Pictured above: Example of false positive (failure to diagnose a normal ECG in patient without AF) electrocardiograms (ECGs) caused by occurrence of premature complexes or bradycardia and false negative (failure to detect AF in a patient with AF) ECGs caused by broad QRS complexes and ventricular pacing (Credit: Canadian Journal of Cardiology).
Patients with PVCs were three times more likely to have false positive AF diagnoses from the smartwatch ECG, and the identification of patients with atrial tachycardia (AT) and atrial flutter (AFL) was very poor.
“These observations are not surprising, as smartwatch automated detection algorithms are based solely on cycle variability,” Dr. Strik noted, explaining 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.”
In an accompanying editorial(opens in new tab/window), Andrés F. Miranda-Arboleda, MD, and Adrian Baranchuk, MD, Division of Cardiology, Kingston Health Science Center, Kingston, ON, Canada, observed that this is the first “real-world” study focusing on the use of the Apple Watch 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,” Dr. Miranda-Arboleda and Dr. Baranchuk said.
“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,” Dr Strik said. “Smartwatch detection of AF has great potential, but it is more challenging in patients with pre-existing cardiac disease.”
Notes for editors
The article is “Role of Coexisting ECG Anomalies in the Accuracy of Smartwatch ECG Detection of Atrial Fibrillation,” by Hugo-Pierre Racine, MD, Marc Strik, MD, PhD, Joske van der Zande, Saer Abu Alrub, MD, Théo Caillol, MD, Michel Haïssaguerre, MD, Sylvain Ploux, MD, PhD, and Pierre Bordachar, MD, PhD (https://doi.org/10.1016/j.cjca.2022.08.222(opens in new tab/window)).
The editorial is “Atrial Fibrillation Detection by Smartwatch Devices in Patients with Underlying ECG Abnormalities: Still Not Smart Enough?” by Andrés F. Miranda-Arboleda, MD, and Adrian Baranchuk, MD (https://doi.org/10.1016/j.cjca.2022.09.007(opens in new tab/window)).
Both articles appear online ahead of the Canadian Journal of Cardiology, volume 38 issue 11 (November 2022) published by Elsevier(opens in new tab/window).
Full text of the articles is available to credentialed journalists upon request. Contact Eileen Leahy at +1 732 238 3628or [email protected](opens in new tab/window) to obtain copies. Journalists wishing to speak to the study’s authors should contact Marc Strik, MD, PhD, at [email protected](opens in new tab/window). To reach the editorial’s authors for comment, contact Adrian Baranchuk, MD, at [email protected](opens in new tab/window).
About the Canadian Journal of Cardiology
The Canadian Journal of Cardiology(opens in new tab/window) is the official journal of the Canadian Cardiovascular Society(opens in new tab/window). It is a vehicle for the international dissemination of new knowledge in cardiology and cardiovascular science, particularly serving as a major venue for the results of Canadian cardiovascular research and Society guidelines. The journal publishes original reports of clinical and basic research relevant to cardiovascular medicine as well as editorials, review articles, case reports, and papers on health outcomes, policy research, ethics, medical history, and political issues affecting practice. www.onlinecjc.ca(opens in new tab/window)
About the Editor-in-Chief
Editor-in-Chief Stanley Nattel, MD, is Paul-David Chair in Cardiovascular Electrophysiology and Professor of Medicine at the University of Montreal and Director of the Electrophysiology Research Program at the Montreal Heart Institute Research Center.
About the Canadian Cardiovascular Society (CCS)
The CCS(opens in new tab/window) is the national voice for cardiovascular clinicians and scientists, representing more than 2,300 cardiologists, cardiac surgeons and other heart health specialists across Canada. We advance heart health for all by setting standards for excellence in heart health and care, building the knowledge and expertise of the heart team, and influencing policy and advocating for the heart health of all Canadians. For further information on the CCS visit https://ccs.ca(opens in new tab/window).
As a global leader in information and analytics, Elsevier helps researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. We do this by facilitating insights and critical decision-making for customers across the global research and health ecosystems. In everything we publish, we uphold the highest standards of quality and integrity. We bring that same rigor to our information analytics solutions for researchers, academic leaders, funders, R&D-intensive corporations, doctors, and nurses.
Elsevier employs 9,000 people worldwide, including over 2,500 technologists. We have supported the work of our research and health partners for more than 140 years. Growing from our roots in publishing, we offer knowledge and valuable analytics that help our users make breakthroughs and drive societal progress. Digital solutions such as ScienceDirect, Scopus, SciVal, ClinicalKey and Sherpath support strategic research management, R&D performance, clinical decision support, medical education, and nursing education. Researchers and healthcare professionals rely on over 2,800 journals, including The Lancet(opens in new tab/window) and Cell(opens in new tab/window); 46,000+ eBook titles; and iconic reference works, such as Gray's Anatomy. With the Elsevier Foundation(opens in new tab/window) and our external Inclusion & Diversity Advisory Board, we work in partnership with diverse stakeholders to advance inclusion and diversity in science, research and healthcare in developing countries and around the world.
Elsevier is part of RELX(opens in new tab/window), a global provider of information-based analytics and decision tools for professional and business customers.