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Updated: Feb 17, 2026

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System
Published on: April 11, 2025
Transthoracic echocardiographic and artificial intelligence-enabled electrocardiography predictors of atrial
Dylan Goings1, Ikram U Haq2, Arman Arghami2
1Department of Internal Medicine Mayo Clinic, Rochester, Minnesota.
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.
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