1. Artificial intelligence estimated electrocardiographic age as a recurrence predictor after atrial fibrillation catheter ablation.
- Author
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Park, Hanjin, Kwon, Oh-Seok, Shim, Jaemin, Kim, Daehoon, Park, Je-Wook, Kim, Yun-Gi, Yu, Hee Tae, Kim, Tae-Hoon, Uhm, Jae-Sun, Choi, Jong-Il, Joung, Boyoung, Lee, Moon-Hyoung, and Pak, Hui-Nam
- Subjects
PREOPERATIVE period ,RISK assessment ,PREDICTION models ,RESEARCH funding ,ARTIFICIAL intelligence ,FISHER exact test ,KRUSKAL-Wallis Test ,AGE distribution ,DESCRIPTIVE statistics ,CHI-squared test ,ELECTROCARDIOGRAPHY ,ATRIAL fibrillation ,RESEARCH methodology ,DISEASE relapse ,CATHETER ablation ,CONFIDENCE intervals ,DATA analysis software ,ALGORITHMS ,MYOCARDIAL depressants ,DISEASE risk factors - Abstract
The application of artificial intelligence (AI) algorithms to 12-lead electrocardiogram (ECG) provides promising age prediction models. We explored whether the gap between the pre-procedural AI-ECG age and chronological age can predict atrial fibrillation (AF) recurrence after catheter ablation. We validated a pre-trained residual network-based model for age prediction on four multinational datasets. Then we estimated AI-ECG age using a pre-procedural sinus rhythm ECG among individuals on anti-arrhythmic drugs who underwent de-novo AF catheter ablation from two independent AF ablation cohorts. We categorized the AI-ECG age gap based on the mean absolute error of the AI-ECG age gap obtained from four model validation datasets; aged-ECG (≥10 years) and normal ECG age (<10 years) groups. In the two AF ablation cohorts, aged-ECG was associated with a significantly increased risk of AF recurrence compared to the normal ECG age group. These associations were independent of chronological age or left atrial diameter. In summary, a pre-procedural AI-ECG age has a prognostic value for AF recurrence after catheter ablation. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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