Abstract 16672: Determining the Diagnostic Yield for Atrial Fibrillation Using Continuous Smartwatch Monitoring

Abstract

Introduction: Smartwatch technologies become ubiquitous in our daily life and can contribute to better health. The optical sensing element (photoplethysmography or PPG) enables continuous heart rate and heart rhythm monitoring. However, signal quality is a major challenge to overcome to improve the diagnostic yield. Hypothesis: To compare the diagnostic yield of AF detection between traditional 24h Holter and continuous wearable monitoring. Methods: In this study, patients receiving a diagnostic 24h ECG Holter monitor were parallel provided with a wearable smartwatch device capable of continuous PPG logging. Data was recorded up to 24 hours and the ECG and PPG signals were synchronized. The PPG signals were analyzed by the FibriCheck algorithms and compared towards the Holter analysis results. Results: In total, 100 patients participated in the study with a mean age of 60±13 years and 53.8% was male. Over 142,560 minutes of data have been collected from both Holter and wearable device. On average, 45% of the data was labeled as insufficient quality. There was a significant (P<0.001) difference in presence of bad quality between day (47.5%) and night (10.6%). In total, on Holter, 9.6% of the data was labelled as atrial fibrillation, while on the PPG signal only 6.5% AF was found. Missing AF occurred during episodes of insufficient quality, impacting the diagnostic yield. Without a quality detection system, a over-diagnostic rate of 48.1% AF was observed. Conclusions: Initial results indicate the feasibility of continuous heart rhythm monitoring using wearable systems. However, optimizing the diagnostic yield remains a challenge. Diagnostic results obtained during the night are in high agreement between Holter and wearable.