Wearable Smartwatches for Atrial Fibrillation Detection and Burden Estimation After Ablation: Comparison With Continuous Monitoring

BACKGROUND: Wearable ECG-enabled smartwatches have been validated for atrial fibrillation (AF) screening, but their accuracy for monitoring AF recurrence and quantifying AF burden after catheter ablation is uncertain. OBJECTIVES: To evaluate the simulated performance of three commercial smartwatch algorithms for AF recurrence detection and AF burden estimation compared with implantable cardiac monitors (ICMs). METHODS: Using continuous ICM data from 346 patients in the CIRCA-DOSE trial, we simulated three smartwatch algorithms, assuming daytime wear (8:00 AM-10:00 PM). We also simulated commonly-used non-invasive intermittent rhythm monitoring strategies. Primary endpoints were sensitivity for arrhythmia recurrence and correlation with ICM-derived AF burden. Analyses were stratified by daily wear time and patient activity. RESULTS: AF recurrence occurred in 47.1% of patients. Simulated detection sensitivities were 82.2% (Apple Watch AF Burden), 70.6% (Apple Watch IRN), and 64.4% (Fitbit IHRD), compared with 15.8%-64.6% for simulated intermittent AECG monitors. Wearables outperformed commonly-used Holter/patch monitoring strategies. AF burden correlation with ICM exceeded r = 0.97 for all algorithms. Among missed recurrences, median AF burden was <0.02%. Longer daily wear improved sensitivity (>90% with 24-hour use), whereas patient activity modestly reduced detection. CONCLUSIONS: Smartwatch-based AF detection algorithms demonstrate strong correlation with ICM-derived AF burden and clinically good sensitivity for recurrence detection, outperforming conventional non-invasive strategies. These findings support the integration of wearables as a scalable alternative for post-ablation rhythm monitoring.