1. AI-enabled ECG index for predicting left ventricular dysfunction in patients with ST-segment elevation myocardial infarction.
- Author
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Jeon KH, Lee HS, Kang S, Jang JH, Jo YY, Son JM, Lee MS, Kwon JM, Kwun JS, Cho HW, Kang SH, Lee W, Yoon CH, Suh JW, Youn TJ, and Chae IH
- Subjects
- Humans, Male, Female, Middle Aged, Aged, Prognosis, Percutaneous Coronary Intervention, Algorithms, ST Elevation Myocardial Infarction complications, ST Elevation Myocardial Infarction physiopathology, ST Elevation Myocardial Infarction diagnosis, ST Elevation Myocardial Infarction surgery, Electrocardiography, Ventricular Dysfunction, Left physiopathology, Ventricular Dysfunction, Left diagnosis, Artificial Intelligence
- Abstract
Electrocardiogram (ECG) changes after primary percutaneous coronary intervention (PCI) in ST-segment elevation myocardial infarction (STEMI) patients are associated with prognosis. This study investigated the feasibility of predicting left ventricular (LV) dysfunction in STEMI patients using an artificial intelligence (AI)-enabled ECG algorithm developed to diagnose STEMI. Serial ECGs from 637 STEMI patients were analyzed with the AI algorithm, which quantified the probability of STEMI at various time points. The time points included pre-PCI, immediately post-PCI, 6 h post-PCI, 24 h post-PCI, at discharge, and one-month post-PCI. The prevalence of LV dysfunction was significantly associated with the AI-derived probability index. A high probability index was an independent predictor of LV dysfunction, with higher cardiac death and heart failure hospitalization rates observed in patients with higher indices. The study demonstrates that the AI-enabled ECG index effectively quantifies ECG changes post-PCI and serves as a digital biomarker capable of predicting post-STEMI LV dysfunction, heart failure, and mortality. These findings suggest that AI-enabled ECG analysis can be a valuable tool in the early identification of high-risk patients, enabling timely and targeted interventions to improve clinical outcomes in STEMI patients., (© 2024. The Author(s).)
- Published
- 2024
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