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P-Wave Beat-to-Beat Analysis to Predict Atrial Fibrillation Recurrence after Catheter Ablation

Authors :
Dimitrios Tachmatzidis
Anastasios Tsarouchas
Dimitrios Mouselimis
Dimitrios Filos
Antonios P. Antoniadis
Dimitrios N. Lysitsas
Nikolaos Mezilis
Antigoni Sakellaropoulou
Georgios Giannopoulos
Constantinos Bakogiannis
Konstantinos Triantafyllou
Nikolaos Fragakis
Konstantinos P. Letsas
Dimitrios Asvestas
Michael Efremidis
Charalampos Lazaridis
Ioanna Chouvarda
Vassilios P. Vassilikos
Source :
Diagnostics, Vol 12, Iss 4, p 830 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

The identification of patients prone to atrial fibrillation (AF) relapse after catheter ablation is essential for better patient selection and risk stratification. The current prospective cohort study aims to validate a novel P-wave index based on beat-to-beat (B2B) P-wave morphological and wavelet analysis designed to detect patients with low burden AF as a predictor of AF recurrence within a year after successful catheter ablation. From a total of 138 consecutive patients scheduled for AF ablation, 12-lead ECG and 10 min vectorcardiogram (VCG) recordings were obtained. Univariate analysis revealed that patients with higher B2B P-wave index had a two-fold risk for AF recurrence (HR: 2.35, 95% CI: 1.24–4.44, p: 0.010), along with prolonged P-wave, interatrial block, early AF recurrence, female gender, heart failure history, previous stroke, and CHA2DS2-VASc score. Multivariate analysis of assessable predictors before ablation revealed that B2B P-wave index, along with heart failure history and a history of previous stroke or transient ischemic attack, are independent predicting factors of atrial fibrillation recurrence. Further studies are needed to assess the predictive value of the B2B index with greater accuracy and evaluate a possible relationship with atrial substrate analysis.

Details

Language :
English
ISSN :
20754418
Volume :
12
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Diagnostics
Publication Type :
Academic Journal
Accession number :
edsdoj.888b234ee2e74857ae55eb56b977374b
Document Type :
article
Full Text :
https://doi.org/10.3390/diagnostics12040830