多站点,外部验证一个人工智能支持的心电图算法,用于检测低射出分数.
Rickey E Carter1, Patrick W Johnson1, Jordan B Strom2
1Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, Florida, USA.
JACC. Advances
|January 17, 2026
概括
基于人工智能的心电图查 (ECG-AI) 有效地检测左下心室喷射率 (LEF). 这种经过验证的软件显示出高准确性,可能减少某些患者对心声回声图的需求.
科学领域:
- 心脏病学 心脏病学
- 医疗器械 医疗器械
- 人工智能的人工智能
背景情况:
- 低左心室喷射分数 (LEF) 往往没有被诊断出来.
- 基于人工智能的心电图 (ECG-AI) 查为LEF检测提供了一个可扩展的解决方案.
研究的目的:
- 验证一个全面的ECG-AI软件作为用于识别LEF的医疗器械.
- 在现实临床环境中评估ECG-AI的诊断性能.
主要方法:
- 利用了来自美国四个不同地点的数据,包括30天内进行的心电图和胸前心电图.
- 从13,960名患者的电子健康记录中提取和分析.
主要成果:
- 电脑心电图-人工智能显示出强大的诊断准确性,AUROC为0.92.
- 对于LEF检测,灵敏度为84.5%,特异性为83.6%.
- 积极的预测值为30.5%,负的预测值为98.4%.
结论:
- 外部验证证实了该算法在多样化的患者群体中强大的诊断性能.
- 电脑心电图-人工智能的高负预测值表明它作为排除策略的实用性,可能会推迟心电图.
- 这项研究验证了ECG-AI软件用于LEF检测,强调了其临床适用性.
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