Transthoracic echocardiographic and artificial intelligence-enabled electrocardiography predictors of atrial arrhythmia recurrence after surgical ablation

Background Recurrence of atrial fibrillation (AF)/flutter (AFl) after surgical ablation remains difficult to predict. Integration of novel biomarkers may enhance risk stratification. Objective This study aimed to assess whether combining preoperative transthoracic echocardiography (TTE) and artificial intelligence-enabled electrocardiography (AI-ECG) scores improves the prediction of AF/AFl recurrence after surgical ablation. Methods We retrospectively analyzed 1696 patients who underwent surgical AF/AFl ablation from 2006 to 2025 with available preoperative TTE and ECG and postblanking (90-day) ECG follow-up. Clinical, TTE, and AI-ECG variables (AF probability, ECG-estimated age, heart failure with preserved ejection fraction, left ventricular dysfunction, and aortic stenosis scores) were assessed. Cox proportional hazards and random survival forest models (80:20 train-test split) identified predictors of recurrence. Results Among 1696 patients (mean age 67.3 ± 10.2 years; 61.7% male), 949 (56%) had AF/AFl recurrence over a median 3.14-year follow-up. Patients with recurrence had larger left atrial area (30.4 vs 24.5 cm²), elevated mitral E-wave velocity (1.015 vs 0.896 m/s), and adverse AI-ECG biomarkers for AF probability, ECG-estimated age, heart failure with preserved ejection fraction, left ventricular dysfunction, and aortic stenosis (all P < .001). In multivariable analysis, independent predictors of recurrence included higher ECG-AF probability ( P < .0001), older ECG-estimated age ( P = .0002), left atrial area ( P = .046), body mass index ( P = .036), and diastolic blood pressure (hazard ratio 1.008/mm Hg; P = .010). The final Cox model achieved a concordance index of ∼0.67 and a 3-year Brier score of 0.21, with 3-year freedom-from-arrhythmia rates of ∼85% vs ∼43% for the lowest- vs highest-risk quartiles. Random survival forest modeling yielded a slightly higher concordance index (∼0.69). Conclusion Preoperative AI-ECG biomarkers (AF probability, age discordance) and TTE markers of atrial remodeling independently predicted AF/AFl recurrence after surgical AF/AFl ablation. Integration of these metrics improved risk stratification.