Artificial intelligence software standardizes electrogram‐based ablation outcome for persistent atrial fibrillation.
Introduction: 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...
| Publicado en: | Journal of Cardiovascular Electrophysiology Vol. 33; no. 11; pp. 2250 - 2261 |
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| Autores principales: | , , , , , , , , , , , , , , , , , , , |
| Formato: | clinical trial diagnostic images pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Nov2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=160149553&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 160149553 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10453873 GSB jtl: Journal of Cardiovascular Electrophysiology issn: 10453873 maglogo: Y pubinfo: dt: Nov2022 vid: 33 iid: 11 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 160149553 159132215 160149553 160149553 10.1111/jce.15657 160149553 ppf: 2250 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: C – @attributes: type: P tig: atl: Artificial intelligence software standardizes electrogram‐based ablation outcome for persistent atrial fibrillation. aug: au: Seitz, Julien Durdez, Théophile Mohr Albenque, Jean P. Pisapia, André Gitenay, Edouard Durand, Cyril Monteau, Jacques Moubarak, Ghassan Théodore, Guillaume Lepillier, Antoine Zhao, Alexandre Bremondy, Michel Maluski, Alexandre Cauchemez, Bruno Combes, Stéphane Guyomar, Yves Heuls, Sébastien Thomas, Olivier Penaranda, Guillaume Siame, Sabrina affil: St. Joseph Hospital, Marseille, France sug: subj: Artificial Intelligence Utilization Software Utilization Catheter Ablation Methods Chronic Disease Surgery Atrial Fibrillation Surgery Surgery, Computer-Assisted Methods Electrophysiology Methods Treatment Outcomes Evaluation Human Male Female Middle Age Aged Cardiac Patients Surgical Patients Prospective Studies Multicenter Studies Nonrandomized Trials Clinical Trials Pilot Studies Descriptive Statistics Comparative Studies Antiarrhythmia Agents Therapeutic Use Body Surface Potential Mapping Inpatients Heart Function Tests Methods Atrial Fibrillation Diagnosis Middle Aged: 45-64 years Aged: 65+ years Male Female ab: Introduction: 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. Methods: 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. Results: 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. Conclusion: 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. pubtype: Academic Journal doctype: clinical trial diagnostic images pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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