人工智能应用于心电图来排除急性心肌梗塞:ROMIAE多中心研究
Min Sung Lee1,2, Tae Gun Shin3, Youngjoo Lee4
1Medical AI Co., Ltd., 13F, 38, Yeongdong-daero 85-gil, Gangnam-gu, Seoul 06180, Republic of Korea.
European heart journal
|February 24, 2025
概括
人工智能增强心电图 (AI-ECG) 显示了急性心肌梗塞 (AMI) 在急诊室的强烈诊断准确性. 这种人工智能工具还有效地预测了主要的不良心血管事件 (MACE),与传统方法相匹配或超过.
科学领域:
- 心脏病学 心脏病学
- 人工智能的人工智能
- 医学诊断 医学诊断 医学诊断
背景情况:
- 新出现的证据表明,人工智能增强型心电图 (AI-ECG) 可以检测急性心肌梗塞 (AMI).
- 在急诊室 (ED) 设置中AI-ECG的现实世界验证对于其临床采用至关重要.
研究的目的:
- 评估AI-ECG在诊断急诊部内 AMI 的诊断性能.
- 评估AI-ECG对30天主要不良心血管事件 (MACE) 的预测能力.
主要方法:
- 未来的队列研究 (ROMIAE) 涉及韩国18家医院 (2022年3月至2023年10月).
- 包括在怀疑AMI的症状发作后24小时内提交ED的成年患者.
- 将AI-ECG得分与HEART得分,GRACE 2.0得分,热素水平和医生评估进行了比较.
主要成果:
- AI-ECG显示,用于AMI检测,接收器操作特征曲线 (AUC) 下的面积为0.878,相当于HEART得分 (0.877).
- 对于30天的MACE预测,AI-ECG的AUC为0.866,类似于HEART得分 (0.858).
- 与AI-ECG集成改善了风险分层,与单独的HEART得分相比,净重新分类改善了19.6%.
结论:
- AI-ECG在ED中表现出显著的诊断准确性和AMI和30天MACE的预测能力.
- AI-ECG的性能与传统的风险分层方法和医生的判断相美或优越.
- 这项研究支持AI-ECG在紧急护理中对心血管事件检测的实际实用性.
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