Artificial intelligence applied to electrocardiogram to rule out acute myocardial infarction: the ROMIAE multicentre study.

IF 37.6 1区医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS

European Heart Journal Pub Date : 2025-02-24 DOI:10.1093/eurheartj/ehaf004

Min Sung Lee, Tae Gun Shin, Youngjoo Lee, Dong Hoon Kim, Sung Hyuk Choi, Hanjin Cho, Mi Jin Lee, Ki Young Jeong, Won Young Kim, Young Gi Min, Chul Han, Jae Chol Yoon, Eujene Jung, Woo Jeong Kim, Chiwon Ahn, Jeong Yeol Seo, Tae Ho Lim, Jae Seong Kim, Jeff Choi, Joon-Myoung Kwon, Kyuseok Kim

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引用次数: 0

Abstract

Background and aims: Emerging evidence supports artificial intelligence-enhanced electrocardiogram (AI-ECG) for detecting acute myocardial infarction (AMI), but real-world validation is needed. The aim of this study was to evaluate the performance of AI-ECG in detecting AMI in the emergency department (ED).

Methods: The Rule-Out acute Myocardial Infarction using Artificial intelligence Electrocardiogram analysis (ROMIAE) study is a prospective cohort study conducted in the Republic of Korea from March 2022 to October 2023, involving 18 university-level teaching hospitals. Adult patients presenting to the ED within 24 h of symptom onset concerning for AMI were assessed. Exposure included AI-ECG score, HEART score, GRACE 2.0 score, high-sensitivity troponin level, and Physician AMI score. The primary outcome was diagnosis of AMI during index admission, and the secondary outcome was 30 day major adverse cardiovascular event (MACE).

Results: The study population comprised 8493 adults, of whom 1586 (18.6%) were diagnosed with AMI. The area under the receiver operating characteristic curve for AI-ECG was 0.878 (95% CI, 0.868-0.888), comparable with the HEART score (0.877; 95% CI, 0.869-0.886) and superior to the GRACE 2.0 score, high-sensitivity troponin level, and Physician AMI score. For predicting 30 day MACE, AI-ECG (area under the receiver operating characteristic, 0.866; 95% CI, 0.856-0.877) performed comparably with the HEART score (0.858; 95% CI, 0.848-0.868). The integration of the AI-ECG improved risk stratification and AMI discrimination, with a net reclassification improvement of 19.6% (95% CI, 17.38-21.89) and a C-index of 0.926 (95% CI, 0.919-0.933), compared with the HEART score alone.

Conclusions: In this multicentre prospective study, the AI-ECG demonstrated diagnostic accuracy and predictive power for AMI and 30 day MACE, which was similar to or better than that of traditional risk stratification methods and ED physicians.

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背景和目的：新的证据支持人工智能增强心电图（AI-ECG）检测急性心肌梗死（AMI），但还需要实际验证。本研究旨在评估人工智能心电图在急诊科（ED）中检测急性心肌梗死的性能：利用人工智能心电图分析排除急性心肌梗死（Rule-Out acute Myocardial Infarction using Artificial Intelligence Electrocardiogram Analysis，ROMIAE）研究是一项前瞻性队列研究，于 2022 年 3 月至 2023 年 10 月在大韩民国进行，涉及 18 所大学教学医院。研究对象为在急性心肌梗死症状出现后 24 小时内到急诊室就诊的成人患者。暴露指标包括 AI-ECG 评分、HEART 评分、GRACE 2.0 评分、高敏肌钙蛋白水平和医师 AMI 评分。主要结果是入院时诊断为急性心肌梗死，次要结果是 30 天内的主要不良心血管事件（MACE）：研究对象包括 8493 名成年人，其中 1586 人（18.6%）被诊断为急性心肌梗死。AI-ECG的接收器操作特征曲线下面积为0.878（95% CI，0.868-0.888），与HEART评分（0.877；95% CI，0.869-0.886）相当，优于GRACE 2.0评分、高敏肌钙蛋白水平和医师AMI评分。在预测 30 天 MACE 方面，AI-ECG（接收器操作特征下面积，0.866；95% CI，0.856-0.877）的表现与 HEART 评分（0.858；95% CI，0.848-0.868）相当。与单独使用 HEART 评分相比，整合 AI-ECG 提高了风险分层和 AMI 鉴别能力，净重新分类率提高了 19.6% (95% CI, 17.38-21.89)，C 指数为 0.926 (95% CI, 0.919-0.933)：在这项多中心前瞻性研究中，AI-ECG 显示了对 AMI 和 30 天 MACE 的诊断准确性和预测能力，与传统的风险分层方法和急诊室医生的诊断准确性和预测能力相似或更好。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

European Heart Journal 医学-心血管系统

CiteScore

39.30

自引率

6.90%

发文量

3942

审稿时长

1 months

期刊介绍： The European Heart Journal is a renowned international journal that focuses on cardiovascular medicine. It is published weekly and is the official journal of the European Society of Cardiology. This peer-reviewed journal is committed to publishing high-quality clinical and scientific material pertaining to all aspects of cardiovascular medicine. It covers a diverse range of topics including research findings, technical evaluations, and reviews. Moreover, the journal serves as a platform for the exchange of information and discussions on various aspects of cardiovascular medicine, including educational matters. In addition to original papers on cardiovascular medicine and surgery, the European Heart Journal also presents reviews, clinical perspectives, ESC Guidelines, and editorial articles that highlight recent advancements in cardiology. Additionally, the journal actively encourages readers to share their thoughts and opinions through correspondence.