Jeon Ki-Hyun, Lee Hak Seung, Kang Sora, Jang Jong-Hwan, Jo Yong-Yeon, Son Jeong Min, Lee Min Sung, Kwon Joon-Myoung, Kwun Ju-Seung, Cho Hyoung-Won, Kang Si-Hyuck, Lee Wonjae, Yoon Chang-Hwan, Suh Jung-Won, Youn Tae-Jin, Chae In-Ho
Department of Internal Medicine, Seoul National University College of Medicine and Department of Cardiology, Seoul National University Bundang Hospital, Seongnam, South Korea.
Medical AI Co., Ltd, Seoul, South Korea.
Sci Rep. 2024 Jul 17;14(1):16575. doi: 10.1038/s41598-024-67532-6.
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.
ST段抬高型心肌梗死（STEMI）患者接受直接经皮冠状动脉介入治疗（PCI）后的心电图（ECG）变化与预后相关。本研究调查了使用一种为诊断STEMI而开发的人工智能（AI）心电图算法预测STEMI患者左心室（LV）功能障碍的可行性。利用该AI算法分析了637例STEMI患者的系列心电图，该算法可量化不同时间点STEMI的发生概率。时间点包括PCI术前、PCI术后即刻、PCI术后6小时、PCI术后24小时、出院时以及PCI术后1个月。LV功能障碍的患病率与AI得出的概率指数显著相关。高概率指数是LV功能障碍的独立预测因素，指数较高的患者心脏死亡和心力衰竭住院率更高。该研究表明，基于AI的心电图指数可有效量化PCI术后的心电图变化，并作为一种数字生物标志物，能够预测STEMI后LV功能障碍、心力衰竭和死亡率。这些发现表明，基于AI的心电图分析可成为早期识别高危患者的有价值工具，从而能够及时进行有针对性的干预，改善STEMI患者的临床结局。
