Validation of a machine learning algorithm to identify pulmonary vein isolation during ablation procedures for the treatment of atrial fibrillation: results of the PVISION study.

Journal: Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
PMID: 38682165

Abstract

AIMS: Pulmonary vein isolation (PVI) is the cornerstone of ablation for atrial fibrillation. Confirmation of PVI can be challenging due to the presence of far-field electrograms (EGMs) and sometimes requires additional pacing manoeuvres or mapping. This prospective multicentre study assessed the agreement between a previously trained automated algorithm designed to determine vein isolation status with expert opinion in a real-world clinical setting.

Authors

  • Jan De Pooter
    Department of Cardiology, Ghent University Hospital, Ghent, Belgium.
  • Liesbeth Timmers
    Heart Center, UZ Ghent, Corneel Heymanslaan 10, 9000 Ghent, Belgium.
  • Serge Boveda
    Clinique Pasteur, Toulouse, France.
  • Stephane Combes
    Clinique Pasteur, Toulouse, France.
  • Sebastien Knecht
    AZ Sint-Jan, Brugge, Belgium.
  • Alexandre Almorad
    Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing Universitair Ziekenhuis Brussel, Vrije Universiteit Brussel, European Reference Networks Guard-Heart Brussels Belgium.
  • Carlos De Asmundis
    UZ Brussel, Brussels, Belgium.
  • Mattias Duytschaever
    Department of Cardiology, Ghent University Hospital, Ghent, Belgium.

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