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Recurring patterns of atrial fibrillation in surface ECG predict restoration of sinus rhythm by catheter ablation

Lookup NU author(s): Dr Luigi Di Marco, Dr Daniel Raine, Dr John Bourke, Dr Philip Langley

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Abstract

Background: Non-invasive tools to help identify patients likely to benefit from catheter ablation (CA) of atrial fibrillation (AF) would facilitate personalised treatment planning. Aim: To investigate atrial waveform organisation through recurrence plot indices (RPI) and their ability to predict CA outcome.Methods: One minute 12-lead ECG was recorded before CA from 62 patients with AF (32 paroxysmal AF; 45 men; age 57 +/- 10 years). Organisation of atrial waveforms from i) TQ intervals in V-1 and ii) QRST suppressed continuous AF waveforms (CAFW), were quantified using RPI: percentage recurrence (PR), percentage determinism (PD), entropy of recurrence (ER). Ability to predict acute (terminating vs. non-terminating AF), 3-month and 6-month postoperative outcome (AF vs. AF free) were assessed.Results: RPI either by TQ or CAFW analysis did not change significantly with acute outcome. Patients arrhythmia-free at 6-month follow-up had higher organisation in TQ intervals by PD (p < 0.05) and ER (p < 0.005) and both were significant predictors of 6-month outcome (PD (AUC = 0.67, p < 0.05) and ER (AUC = 0.72, p < 0.005)). For paroxysmal AF cases, all RPI predicted 3-month (AUC(ER) = 0.78, p < 0.05; AUC(PD) = 0.79, p < 0.05; AUC(PR) = 0.80, p < 0.01) and 6-month (AUC(ER) = 0.81, p < 0.005: AUC(PD) = 0.75, p < 0.05; AUC(PR) = 0.71, p < 0.05) outcome. CAFW-derived RPIs did not predict acute or postoperative outcomes.Higher values of any RPI from TQ (values greater than 25th percentile of preoperative distribution) were associated with decreased risk of AF relapse at follow-up (hazard ratio <= 0.52, all p < 0.05).Conclusions: Recurring patterns from preprocedural 1-minute recordings of ECG TQ intervals were significant predictors of CA 6-month outcome. (C) 2014 Elsevier Ltd. All rights reserved.


Publication metadata

Author(s): Di Marco LY, Raine D, Bourke JP, Langley P

Publication type: Article

Publication status: Published

Journal: Computers in Biology and Medicine

Year: 2014

Volume: 54

Pages: 172-179

Print publication date: 01/11/2014

Online publication date: 21/09/2014

Acceptance date: 12/09/2014

ISSN (print): 0010-4825

ISSN (electronic): 1879-0534

Publisher: PERGAMON-ELSEVIER SCIENCE LTD

URL: http://dx.doi.org/10.1016/j.compbiomed.2014.09.005

DOI: 10.1016/j.compbiomed.2014.09.005

PubMed id: 25282707


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