Key result
Persistent symptoms affect ~51% of patients after AF ablation, defining distinct sub-phenotypes linked to recurrence.
Why the study?
Persistent symptoms following AF ablation are common independently of AF recurrence, but clinically relevant symptom-based sub-phenotypes had not been identified.
Can smartphone app-based symptom and rhythm monitoring identify distinct symptom clusters in patients after atrial fibrillation ablation?
Observational (n=614)
Can smartphone app-based symptom and rhythm monitoring identify distinct symptom clusters in patients after atrial fibrillation ablation?
Smartphone app-based monitoring identifies distinct symptom clusters in post-AF ablation patients that correlate with clinical characteristics and AF recurrence, potentially guiding individualized management.
Answers are grounded in this paper and cite their sources.
Symptoms after AF ablation are common; leaves open whether symptom monitoring improves recurrence detection or outcomes.
Background Atrial fibrillation (AF) is characterised by a heterogeneous presentation of symptoms. AF ablation reduces symptom burden. However, persistent symptoms following AF ablation are common independently of AF recurrence. Purpose to perform a cluster analysis to identify clinically relevant AF sub-phenotypes based on persistent symptoms following AF ablation and evaluate their associations with clinical characteristics and AF recurrence. Methods Patients were instructed to perform smartphone app-based simultaneous symptom and photoplethysmography heart rhythm monitoring three times daily for one week at the 3-month follow-up after AF ablation. A two-step cluster analysis including seven categorical symptoms variables was performed in symptomatic patients. Results In total, half of all patients (313 of 614 patients, 51%) reported symptoms after AF ablation. Five symptom clusters were identified: 'non-specified symptoms' (n=52, 17%), 'atrial fibrillation with sparse symptoms' (n=93, 30%), 'palpitations' (n=47, 15%), 'fatigue with comorbidities' (n=63, 20%), and 'sinus rhythm with severe symptoms' (n=58, 19%). Frequency (p<0.001) and pattern (p<0.001) of symptom reporting as well as AF recurrence (p<0.001), AF load (p<0.001), AF pattern (p=0.002 and p=0.005) and symptom-rhythm correlation (p<0.001) differed between clusters. Furthermore, age (p<0.01), N-terminal pro–B-type natriuretic peptide levels (p<0.01), CHA2DS2VA score (p<0.001) and left atrial volume index (p=0.01) differed between clusters. Conclusion Half of all patients report symptoms after AF ablation. Using cluster analysis five symptom-based AF sub-phenotypes were identified, each with distinct clinical characteristics, biomarker profiles, AF recurrence, AF pattern, AF and symptom burden and symptom-rhythm correlation. Symptom clusters empowered by digital health may facilitate individualised AF management strategies following AF ablation.
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Sandgren et al. (2026) conducted an observational in Atrial fibrillation (n=614). Persistent symptoms following AF ablation was evaluated on Identification of clinically relevant AF sub-phenotypes based on persistent symptoms. Among 614 patients after AF ablation, 51% reported persistent symptoms, which clustered into five distinct sub-phenotypes differing significantly in AF recurrence (p<0.001) and AF load (p<0.001).
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