Impact of clinical expertise and choice of wearable device on accuracy to detect atrial fibrillation via single-lead ECGs

FUNDING ACKNOWLEDGEMENTS: Type of funding sources: None. BACKGROUND: Manual interpretation of single-lead ECGs (SL-ECG) is often required to confirm a diagnosis of atrial fibrillation (AF). However, accuracy to detect AF via SL-ECGs may vary according to clinical expertise and choice of the wearable device. AIMS: To compare the accuracy to detect AF via single-lead ECG from five different wearable devices (Apple Watch, Fitbit Sense, KardiaMobile, Samsung Galaxy Watch, Withings ScanWatch) between cardiologists, internal medicine (IM) residents, and medical students. METHODS: In this prospective study, invitations to an online survey were distributed via digital invitations among physicians from major Swiss hospitals and medical students from Swiss universities. Participants needed to classify 50 SL-ECGs (from 10 patients and 5 different devices) into three categories: sinus rhythm, AF, or inconclusive. This classification was compared to the diagnosis from an almost simultaneously recorded 12-lead ECG interpreted by two independent cardiologists. In addition, participants were asked to choose the best/worst quality/readability of each manufacturer’s SL-ECG. (Figure A) RESULTS: Overall 450 participants rated 10’865 SL-ECGs. Sensitivity and specificity for the detection of AF via SL-ECG was 75% and 92% for cardiologists, 70% and 86% for IM residents, 55% and 65% for master medical students (year 4-6) and 45% and 58% for bachelor medical students (year 1-3), p<0.001, (Figure A). Participants which stated prior experience in interpreting SL-ECGs demonstrated a sensitivity and specificity of 65% and 81% compared to a sensitivity and specificity of 56% and 67% for participants with no prior experience in interpreting SL-ECGs, p<0.001. Of all participants, 107 rated all 50 ECGs. Diagnostic accuracy of the first five interpreted SL-ECGs was 60% (IQR 40-80%) and diagnostic accuracy of the last five interpreted SL- ECGs was 80% (IQR 60-90%), p<0.001. No significant difference in the accuracy of AF detection was seen between the 5 different wearable devices, p=0.58. 203 participants (45%) and 226 participants (50 %) ranked SL- ECGs from the Apple Watch as the best quality and readability, respectively. CONCLUSION: SL-ECG can be difficult to interpret. Accuracy to correctly identify AF depends on clinical expertise, while the choice of the wearable device seems to have no impact. [Figure: see text]