Apple Watch detection capabilities atrial fibrillation (AF) is heavily influenced by the underlying electro-cardiogram abnormalities such as sinus node dysfunctionatrioventricular (AV) block, or intraventricular conduction delay (IVCD) have been suggested in single-center studies.
Dr. Mark Strick
Clinician and study author Marc Strik, MD, PhD, Bordeaux University Hospital, Pessac, France, said: Medscape Medical News. “this [failure] Most likely it was due to poor trace quality [60%]but in a third of the cases, [34%]which was due to bradycardia and in some cases to tachycardia. [6%].
“I was also surprised to find that the presence of ventricular conduction disease was associated with a higher likelihood of missing atrial fibrillation,” he said.
the study published Online October 11 Canadian Journal of Cardiology.
Anomalies affecting detection
Researchers tested the accuracy of the Apple Watch (Apple, Cupertino, California) in detecting atrial fibrillation in patients with various ECG abnormalities. All participants underwent her 12-lead ECG followed by 30 seconds of his ECG tracking on the Apple Watch Series 5. The smartwatch’s automatic AF detection algorithm gave a result of “no signs of AF”, “AF”, or “no checking for AF”. (Uncategorized)”
Unclassified recordings can be attributed to “low heart rate” (less than 50 beats/min), “high heart rate” (more than 150 beats/min), “poor recording”, or “inconclusive recording”. increase.
Smartwatch recordings were reviewed by a blinded electrophysiologist who interpreted each trace and assigned a diagnosis of ‘AF’, ‘absence of AF’, or ‘diagnosis unknown’. To assess interobserver agreement, a second blinded electrophysiologist interpreted her 100 randomly selected traces.
Of the 734 patients enrolled (mean age 66, 58% male), 539 (73%) had normal sinus rhythm (SR), 154 (21%) had atrial fibrillation, and 33 had atrial fibrillation. It was moving. atrial flutter Also atrial tachycardiaat 3 ventricular tachycardiaand 5 of the junctional tachycardias.
Additionally, 65 (8.9%) had sinus node dysfunction and 21 (2.9%) had secondary or 3rd degree atrioventricular block39 (5.3%) had ventricular pacing rhythm, 54 (7.4%) had premature ventricular contraction (PVC), and 132 (18%) had IVCD (right or left bundle branch block or nonspecific IVCD) .
Of 539 patients with normal SR, 437 records were correctly diagnosed by the smartwatch. Seven were misdiagnosed with AF and 95 were unclassified.
Of the 187 patients with AF, 129 were correctly diagnosed, 17 were misdiagnosed as SR, and 41 were unclassified.
When an unclassified ECG was considered a false result, the smartwatch had a sensitivity of 69% and a specificity of 81% for AF detection. The sensitivity was 88% and the specificity was 98% when the unclassified ECG was excluded from the analysis.
premature atrial contraction (PAC) or PVC (risk ratio [RR]2.9), sinus node dysfunction (RR, 3.71), and AV block (RR, 7.8).
58 patients with atrial fibrillation were classified as SR or inconclusive by smartwatch. Of these, 21 (36%) had her IVCD, 7 (12%) had a ventricular pacing rhythm, and 5 (9%) had her PAC or PVC.
Patients with IVCD (RR, 2.6) and pacing (RR, 2.47) had a higher risk of false-negative traces (missed atrial fibrillation) compared with those without abnormalities.
“powerful tool”
Overall, cardiac electrophysiologists showed high interobserver reproducibility and high agreement in distinguishing between atrial and non-fibrillatory atrial fibrillation. 10% of traces could not be manually diagnosed due to poor ECG quality (3%) or ambiguous her P-waves (7%).
59 of 580 patients with SR were misclassified as AF by experts, and 5 of 154 patients with AF were misclassified as SR.
“Our results indicate that the presence of sinus node dysfunction, second- or third-degree atrioventricular block, ventricular pacing rhythm, PVC, and IVCD are more frequently represented in smartwatch misdiagnosis. “PVC patients were three times more likely to have a false-positive diagnosis of AF.”
Study limitations included the single-center nature of the study and the fact that patients were recruited in the cardiology department. The latter factor may have contributed to his much higher incidence of ECG abnormalities than the average smartwatch user.
“Despite its limitations, smartwatches are still powerful tools for detecting AF and multiple other anomalies,” said Strik. “Missing the diagnosis of atrial fibrillation may not matter so much in real life due to repeated measurements, and the algorithm continues to improve.”
technology improvement
comments on the study of medscapeRichard C. Becker, M.D., Ph.D., Director and Chief Physician, University of Cincinnati Heart, Lung, and Vascular Institute, Cincinnati, Ohio. Facilitates routine use in patient care. It is reassuring to be able to detect atrial fibrillation in the majority of patients with cardiac rhythm abnormalities. ”
Dr. Richard Becker
The findings do not undermine well-conducted studies in healthy individuals of various ages in which atrial fibrillation was accurately detected, he added. Automated diagnostic algorithms for AF, pending optimization and validation in diverse cohorts, should be viewed as communication tools between patients and providers.”
Patients at risk of developing atrial fibrillation could benefit from continuous monitoring using smartwatches, Becker said. “Pre-existing heart rhythm abnormalities must be taken into consideration. To optimally use new technologies, including wearables, we need to understand their performance and limitations. This is best done in partnership with a healthcare provider. ”
Andres F. Miranda-Arboleda, MD, and Adrian Baranchuk, MD, of the Kingston Health Science Center in Ontario, Canada, conclude: accompanying editorial, “In some ways, smartwatch algorithms for detecting atrial fibrillation in cardiovascular disease patients aren’t smart enough yet, but they could be soon.”
This research was supported by the French government. Strik, Miranda-Arboleda, Baranchuk, and Becker report no conflicts of interest.
Kang J. Cardiol. Published online on October 11, 2022. Full text.
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