ArticleJACC. Advances2026
Patient-Led Smartwatch ECG Follow-Up Strategy After AF Ablation: Clinical Trial Design and Implementation.
Article in JACC. Advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Wearable Electrocardiogram Technologies for the Early Detection of Acute Coronary Syndromes.JACC. Asia · 2026Review
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundConventional follow-up after atrial fibrillation (AF) catheter ablation relies on physician-led interval monitoring and often fails to characterize paroxysmal symptoms. An increasing number of patients use smartwatch-based ECG devices for rhythm monitoring, but their structured integration into clinical workflows and the handling of the resultant data are not well described.
objectivesTo describe the design, operationalization, data pipeline, and user engagement of a patient-led smartwatch ECG follow-up strategy after AF ablation within a randomized clinical trial.
methodsA prospective, randomized controlled trial of adults undergoing first-time AF ablation was conducted. Participants were randomized to an Apple Watch-based protocol (daily and symptom-triggered ECGs) or standard follow-up. A prespecified audit of the smartwatch-derived rhythm classification was conducted. User engagement, symptom annotation, and downstream resource use were quantified. Primary clinical outcomes are reported in a companion Brief Report.
resultsOf the 168 enrolled participants (mean age 60.5 ± 9.9 years, 52 (31.0%) female, 84 (50.0%) persistent AF), Active-arm participants recorded a median of 170 (IQR 93-380) ECGs over 12 months and transmitted a median of 1.9% (0.0-8.3) for review. Symptom-annotated ECGs were more likely to show AF compared with unannotated ECGs (OR 16.1, 95% CI 13.0-19.9, P < 0.001) Watch-derived AF and sinus rhythm labels had positive predictive values of 0.96 and 0.95 respectively, although one-third of ECGs were unclassified.
conclusionsA structured, patient-led smartwatch ECG workflow can be embedded into routine post-ablation care with high engagement, modest staff workload, and accurate device-level rhythm classification. This implementation framework provides a practical template for integrating patient-generated wearable data into AF follow-up pathways and future digitally enabled trials.
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