人工智能启用心电图用于心房的识别和增强口服抗凝剂的采用:一个务实的随机临床试验
Wei-Ting Liu1, Chin Lin2,3,4, Chiao-Chin Lee1
1Division of Cardiology, Department of Internal Medicine Tri-Service General Hospital, National Defense Medical Center Taipei Taiwan, R.O.C.
Journal of the American Heart Association
|July 4, 2025
概括
人工智能支持的心电图 (AI-ECG) 警报显著改善了心房 (AF) 诊断和非心脏病学家的非维生素K对抗剂口服抗凝剂处方. 这种AI-ECG干预有助于减少AF护理质量的差异.
科学领域:
- 心脏病学 心脏病学
- 人工智能的人工智能
- 医疗技术 医疗技术 医学技术
背景情况:
- 心房动 (AF) 经常被非心脏病学家低估诊断和治疗.
- 这种差异影响患者的治疗结果,需要创新的诊断解决方案.
研究的目的:
- 评估人工智能支持的ECG (AI-ECG) 警报在改善AF诊断方面的有效性.
- 评估AI-ECG警报对非心脏病学家处方非维生素K对抗剂口服抗凝剂的影响.
主要方法:
- 一项开放标签,集群随机对照试验,涉及台湾两家医院的非心脏病专家.
- 没有先前使用AF或抗凝剂的风险中风患者 (男性CHA2DS2-VASc≥1,女性≥2) 接受了AI-ECG警报或通常的护理.
- 主要终点包括抗凝剂处方,AF诊断,心声图安排和90天内去看心脏病专家.
主要成果:
- 干预组显示,非维生素K抗剂的口服抗凝剂处方率显著更高 (23.3%对12.0%).
- AI-ECG警报导致新的AF诊断率更高 (HR,1.40).
- 在心声图安排,心脏病专家访问或主要心血管不良事件中没有发现显著差异.
结论:
- AI-ECG警报有效地促进非心脏病学家的非维生素K对抗剂口服抗凝剂的处方.
- 这种干预有助于缩小心脏病专家和非心脏病专家之间的AF护理质量差距.
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