Artificial intelligence software standardizes electrogram-based ablation outcome for persistent atrial fibrillation.

ABSTRACT:

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

SUBMITTER: Seitz J 

PROVIDER: S-EPMC9826214 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature