Smartphone Application–Derived Clusters of Persistent Symptoms in Patients After Atrial Fibrillation Ablation

BACKGROUND: Atrial fibrillation (AF) is characterized by a heterogeneous presentation of symptoms. AF ablation reduces symptom burden. However, persistent symptoms following AF ablation are common independently of AF recurrence. OBJECTIVES: This study sought to perform a cluster analysis to identify clinically relevant AF subphenotypes 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 3 times daily for 1 week at the 3-month follow-up after AF ablation. A two-step cluster analysis including 7 categorical symptoms variables was performed in symptomatic patients. RESULTS: -VA score (P < 0.001), and left atrial volume index (P = 0.01) differed between clusters. CONCLUSIONS: Half of all patients report symptoms after AF ablation. Using cluster analysis, 5 symptom-based AF subphenotypes 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 individualized AF management strategies following AF ablation.