Atrial fibrillation phenotypes derived from multimodal data exhibit distinct electrophysiological substrate characteristics, symptom trajectories, and ablation outcomes
Abstract
Aims: 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 characterize the spectrum of pathophysiology present amongst patients classified as having paroxysmal or persistent AF. This study aimed 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 and results: 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. 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.
Conclusion: 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.
Registration: ClinicalTrials.gov Identifier: NCT05057507
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BibTeX
@article{bodagh2026atrial,
title = {{Atrial fibrillation phenotypes derived from multimodal data exhibit distinct electrophysiological substrate characteristics, symptom trajectories, and ablation outcomes}},
author = {Neil Bodagh and Vinush Vigneswaran and Ali Gharaviri and Irum Kotadia and Magda Klis and Nilanka N Mannakkara and Kestutis Maciunas and Arno Von Kietzell and Megan Bell and Hayley Cuthbert and Matthew Wright and John Whitaker and Christopher A Rinaldi and Anoop Shetty and Shaumik Adhya and Gurpreet Dhillon and Roy Jogiya and Una Buckley and David Jones and Zhong Chen and Amedeo Chiribiri and Neil R Grubb and Chris Lang and Cesario Pancinha and Michelle C Williams and Steven Niederer and Shouvik Haldar and Mark O’Neill and Steven E Williams},
journal = {European heart journal open},
year = {2026},
month = sep,
doi = {10.1093/ehjopen/oeag162},
url = {https://europepmc.org/article/PMC/PMC13728345},
note = {CC BY},
}
RIS
TY - JOUR
TI - Atrial fibrillation phenotypes derived from multimodal data exhibit distinct electrophysiological substrate characteristics, symptom trajectories, and ablation outcomes
AU - Neil Bodagh
AU - Vinush Vigneswaran
AU - Ali Gharaviri
AU - Irum Kotadia
AU - Magda Klis
AU - Nilanka N Mannakkara
AU - Kestutis Maciunas
AU - Arno Von Kietzell
AU - Megan Bell
AU - Hayley Cuthbert
AU - Matthew Wright
AU - John Whitaker
AU - Christopher A Rinaldi
AU - Anoop Shetty
AU - Shaumik Adhya
AU - Gurpreet Dhillon
AU - Roy Jogiya
AU - Una Buckley
AU - David Jones
AU - Zhong Chen
AU - Amedeo Chiribiri
AU - Neil R Grubb
AU - Chris Lang
AU - Cesario Pancinha
AU - Michelle C Williams
AU - Steven Niederer
AU - Shouvik Haldar
AU - Mark O’Neill
AU - Steven E Williams
PY - 2026
DA - 2026/09/28
JO - European heart journal open
DO - 10.1093/ehjopen/oeag162
UR - https://europepmc.org/article/PMC/PMC13728345
AB - Aims: 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 characterize the spectrum of pathophysiology present amongst patients classified as having paroxysmal or persistent AF. This study aimed 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 and results: 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. 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. Conclusion: 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. Registration: ClinicalTrials.gov Identifier: NCT05057507
SN - 2752-4191
ER -