title: Recurring patterns of atrial fibrillation in surface ECG predict restoration of sinus rhythm by catheter ablation.
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.
  
  
  OBJECTIVE
  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<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.
authors.affiliation: Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, UK; Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), University of Sheffield, Sheffield, UK. Electronic address: luigiyuri.dimarco@gmail.com.
authors.forename: Luigi Yuri
authors.initials: LY
authors.lastname: Di Marco
authors.affiliation: Department of Cardiology, Freeman Hospital, Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, UK.
authors.forename: Daniel
authors.initials: D
authors.lastname: Raine
authors.affiliation: Department of Cardiology, Freeman Hospital, Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, UK.
authors.forename: John P
authors.initials: JP
authors.lastname: Bourke
authors.affiliation: Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, UK; School of Engineering, University of Hull, Hull, UK.
authors.forename: Philip
authors.initials: P
authors.lastname: Langley
mesh_terms: D000465:Algorithms; D001281:Atrial Fibrillation / Q000175:diagnosis* / Q000601:surgery*; D017115:Catheter Ablation / Q000379:methods*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004562:Electrocardiography / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009991:Oscillometry / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D012008:Recurrence; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016896:Treatment Outcome
keywords: Atrial fibrillation; Electrocardiogram segmentation; Principal component analysis; Recurrence quantification analysis; TQ interval