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Frontiers Media, Frontiers in Cardiovascular Medicine, (9), 2022

DOI: 10.3389/fcvm.2022.879139

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Rationale and Design of the ISOLATION Study: A Multicenter Prospective Cohort Study Identifying Predictors for Successful Atrial Fibrillation Ablation in an Integrated Clinical Care and Research Pathway

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

IntroductionContinuous progress in atrial fibrillation (AF) ablation techniques has led to an increasing number of procedures with improved outcome. However, about 30–50% of patients still experience recurrences within 1 year after their ablation. Comprehensive translational research approaches integrated in clinical care pathways may improve our understanding of the complex pathophysiology of AF and improve patient selection for AF ablation.ObjectivesWithin the “IntenSive mOlecular and eLectropathological chAracterization of patienTs undergoIng atrial fibrillatiOn ablatioN” (ISOLATION) study, we aim to identify predictors of successful AF ablation in the following domains: (1) clinical factors, (2) AF patterns, (3) anatomical characteristics, (4) electrophysiological characteristics, (5) circulating biomarkers, and (6) genetic background. Herein, the design of the ISOLATION study and the integration of all study procedures into a standardized pathway for patients undergoing AF ablation are described.MethodsISOLATION (NCT04342312) is a two-center prospective cohort study including 650 patients undergoing AF ablation. Clinical characteristics and routine clinical test results will be collected, as well as results from the following additional diagnostics: determination of body composition, pre-procedural rhythm monitoring, extended surface electrocardiogram, biomarker testing, genetic analysis, and questionnaires. A multimodality model including a combination of established predictors and novel techniques will be developed to predict ablation success.DiscussionIn this study, several domains will be examined to identify predictors of successful AF ablation. The results may be used to improve patient selection for invasive AF management and to tailor treatment decisions to individual patients.