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

Di Marco, Luigi Yuri; Raine, Daniel; Bourke, John P.; Langley, Philip

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 V1 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

Citation

Di Marco, L. Y., Raine, D., Bourke, J. P., & Langley, P. (2014). Recurring patterns of atrial fibrillation in surface ECG predict restoration of sinus rhythm by catheter ablation. Computers in biology and medicine, 54, 172-179. https://doi.org/10.1016/j.compbiomed.2014.09.005

• Journal Article Type: Article
• Acceptance Date: Sep 12, 2014
• Online Publication Date: Sep 21, 2014
• Publication Date: Nov 1, 2014
• Deposit Date: Mar 18, 2016
• Publicly Available Date: Mar 18, 2016
• Journal: Computers in biology and medicine
• Print ISSN: 0010-4825
• Electronic ISSN: 1879-0534
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 54
• Pages: 172-179
• DOI: https://doi.org/10.1016/j.compbiomed.2014.09.005
• Keywords: Atrial fibrillation; TQ interval; Recurrence quantification analysis; Principal component analysis; Electrocardiogram segmentation
• Public URL: https://hull-repository.worktribe.com/output/433876
• Publisher URL: http://www.sciencedirect.com/science/article/pii/S001048251400256X
• Additional Information: This is an accepted version of an article published in Computers in biology and medicine, 2014, v.54.