Smartphone application-derived clusters of persistent symptoms in patients after atrial fibrillation ablation: data from the ISOLATION study
E Sandgren, K Betz, M Gawalko, A Hermans, Z Habibi, D Verhaert, J M Hendriks, D Den Uijl, S M Chaldoupi, J Luermans, T Lankveld, U Schotten, K Vernooy, M Rienstra, D LinzAbstract
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.