机会性查无症状左心室功能障碍使用心电图人工智能:一个成本效益的方法
Wei-Ting Liu1, Ping-Hsuan Hsieh2, Chin-Sheng Lin1
1Division of Cardiology, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan.
一个支持人工智能 (AI) 的心电图 (ECG) 算法有效检测无症状左心室功能障碍 (LVD). 使用AI-ECG的机会性查具有成本效益,可能降低医疗保健费用.
科学领域:
- 心脏病学 心脏病学
- 人工智能的人工智能
- 公共卫生 公共卫生
背景情况:
- 无症状的左心室功能障碍 (LVD) 对健康构成重大负担.
- 需要一个经过验证的,具有成本效益的查工具,用于无症状的LVD.
- 目前的选方法缺乏广泛的验证和成本效益.
研究的目的:
- 为了前性验证AI-ECG算法用于检测无症状LVD.
- 使用AI-ECG评估机会性LVD查的成本效益.
主要方法:
- 在台湾两家医院进行前性观察性研究.
- AI-ECG算法将患者分为两层,分为LVD风险组.
- 成本效益分析 (ICER,敏感性分析) 将AI-ECG查与没有查进行比较.
主要成果:
- AI-ECG在LVD检测方面显示出高精度 (AUC 0.984,0.945).
- 机会性AI-ECG查为65岁的人提供了负的ICER,为-7439美元.
- 查在91.5%的病例中具有成本效益,在30,000美元的支付意愿门下.
结论:
- AI-ECG对无症状LVD风险分层显示出希望.
- 在门诊机构进行机会性查可以降低医疗保健成本.
- AI-ECG为LVD查提供了一种经过验证和具有成本效益的方法.
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