Artificial intelligence software standardizes electrogram-based ablation outcome for persistent atrial fibrillation.
artificial intelligence
atrial fibrillation
catheter ablation
dispersion
driver
mapping
sinus rhythm
Journal
Journal of cardiovascular electrophysiology
ISSN: 1540-8167
Titre abrégé: J Cardiovasc Electrophysiol
Pays: United States
ID NLM: 9010756
Informations de publication
Date de publication:
11 2022
11 2022
Historique:
revised:
15
04
2022
received:
16
03
2022
accepted:
04
07
2022
pubmed:
23
8
2022
medline:
15
11
2022
entrez:
22
8
2022
Statut:
ppublish
Résumé
Multiple groups have reported on the usefulness of ablating in atrial regions exhibiting abnormal electrograms during atrial fibrillation (AF). Still, previous studies have suggested that ablation outcomes are highly operator- and center-dependent. This study sought to evaluate a novel machine learning software algorithm named VX1 (Volta Medical), trained to adjudicate multipolar electrogram dispersion. This study was a prospective, multicentric, nonrandomized study conducted to assess the feasibility of generating VX1 dispersion maps. In 85 patients, 8 centers, and 17 operators, we compared the acute and long-term outcomes after ablation in regions exhibiting dispersion between primary and satellite centers. We also compared outcomes to a control group in which dispersion-guided ablation was performed visually by trained operators. The study population included 29% of long-standing persistent AF. AF termination occurred in 92% and 83% of the patients in primary and satellite centers, respectively, p = 0.31. The average rate of freedom from documented AF, with or without antiarrhythmic drugs (AADs), was 86% after a single procedure, and 89% after an average of 1.3 procedures per patient (p = 0.4). The rate of freedom from any documented atrial arrhythmia, with or without AADs, was 54% and 73% after a single or an average of 1.3 procedures per patient, respectively (p < 0.001). No statistically significant differences between outcomes of the primary versus satellite centers were observed for one (p = 0.8) or multiple procedures (p = 0.4), or between outcomes of the entire study population versus the control group (p > 0.2). Interestingly, intraprocedural AF termination and type of recurrent arrhythmia (i.e., AF vs. AT) appear to be predictors of the subsequent clinical course. VX1, an expertise-based artificial intelligence software solution, allowed for robust center-to-center standardization of acute and long-term ablation outcomes after electrogram-based ablation.
Identifiants
pubmed: 35989543
doi: 10.1111/jce.15657
pmc: PMC9826214
doi:
Substances chimiques
Anti-Arrhythmia Agents
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
2250-2260Subventions
Organisme : Volta Medical
Organisme : Hopital Saint Joseph
Commentaires et corrections
Type : CommentIn
Informations de copyright
© The Authors. Journal of Cardiovascular Electrophysiology published by Wiley Periodicals LLC.
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