Key result
Pre-ablation multimodal AF phenotyping linked to post-ablation recurrence rates ranging from 19% to 56%.
Why the study?
Heterogeneity in response to catheter ablation among AF patients classified by arrhythmia duration highlights the need for improved phenotyping using multimodal assessment.
Does multimodal phenotyping identify distinct AF subgroups with different post-ablation recurrence rates and symptom trajectories in patients undergoing first-time AF ablation?
Cohort (n=86)
Yes
Does multimodal phenotyping identify distinct AF subgroups with different post-ablation recurrence rates and symptom trajectories in patients undergoing first-time AF ablation?
p-value: p=0.032
Multimodal phenotyping identifies distinct AF subgroups that better predict post-ablation recurrence and symptom trajectories than conventional paroxysmal/persistent classification.
Multimodal phenotyping identifies distinct AF ablation phenotypes with varying outcomes; leaves open whether it refines selection or improves results prospectively.
Background The heterogeneity in response to catheter ablation amongst atrial fibrillation (AF) patients classified according to arrhythmia duration highlights the need for improved phenotyping. Multimodal assessment may better characterise the spectrum of pathophysiology present amongst patients classified as having paroxysmal or persistent AF. Purpose To perform comprehensive multimodal pre-ablation phenotyping in patients undergoing AF ablation and evaluate associations with post-ablation arrhythmia recurrence, symptom burden, and bi-atrial substrate remodelling. Methods In this multicentre prospective cohort study, 86 patients referred for first-time AF ablation (42% persistent AF) underwent pre-ablation phenotyping beyond usual care, incorporating patch-based ambulatory rhythm monitoring, atrial structural and functional MRI assessment, and formal symptom evaluation. Unsupervised K-means clustering was used to derive phenotypes. The primary outcome was 12-month arrhythmia recurrence; secondary analyses assessed symptom trajectories and bi-atrial substrate characteristics. Results Four AF phenotypes were identified. Arrhythmia recurrence occurred in 56.0%, 42.9%, 22.2%, and 19.0% of patients in Phenotypes 1–4, respectively (log-rank p=0.032). Symptom trajectories differed across phenotypes, with the greatest improvements observed in Phenotypes 3 and 4. Exploratory electroanatomic mapping analyses demonstrated significant between-phenotype differences in bi-atrial bipolar voltage aligned with clinical trajectories. Importantly, phenotypes were not fully explained by conventional classification: Phenotype 2 experienced relatively high recurrence despite comprising predominantly paroxysmal AF patients whilst Phenotype 3 demonstrated favourable outcomes despite a high prevalence of persistent AF. Conclusions Multimodal phenotyping identified distinct AF subgroups associated with differences in post-ablation recurrence, symptom trajectories, and electrophysiological substrate. This approach could improve pre-ablation risk stratification and shared decision-making.
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Bodagh et al. (2026) conducted a cohort in Atrial fibrillation (n=86). Multimodal pre-ablation phenotyping (4 AF phenotypes) vs. Between-phenotype comparison was evaluated on 12-month arrhythmia recurrence (p=0.032). Four distinct AF phenotypes derived from multimodal pre-ablation data were associated with significantly different 12-month arrhythmia recurrence rates ranging from 19.0% to 56.0% (p=0.032).
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