基于社区的心血管风险评估使用心脏TMAI测试:一个前性队列研究
Simon V Rudland1, Nisar H Shah2, Alan Nevill3
1Integrated Care Academy, University of Suffolk, Ipswich, United Kingdom s.rudland@nhs.net.
BJGP open
|May 19, 2025
概括
卡迪西奥测试有效地识别社区环境中高风险个体的心血管疾病. 这种由人工智能驱动的工具比传统的心电图提供了比传统的心电图更有效的临床查.
科学领域:
- 心脏病学 心脏病学
- 医疗保健中的人工智能
- 公共卫生 公共卫生
背景情况:
- 心血管疾病 (CVD) 造成了严重的健康负担,特别是在服务不足的人群中.
- 由于进入障碍,心血管疾病诊断和护理方面的健康不平等仍然存在.
- 基于社区的创新测试技术可以帮助弥合这些差距.
研究的目的:
- 评估卡迪西奥测试检测无症状心血管疾病的能力.
- 评估基于云计算的AI算法解释3D矢量心脏学的实用性.
- 探索一种新的方法,以社区为基础的心血管查.
主要方法:
- 在全科医院,药房和社区卫生中心进行的前性队列研究.
- 招募具有高心血管疾病风险的无症状成年人 (≥18岁) (QRISK3评分≥10%).
- 使用五个电极进行10分钟的Cardisio测试,结果由AI分为红色,珀色或绿色类别.
主要成果:
- 对18至75岁的成年人进行了628次测试,51%是男性.
- 在"红色"卡迪西奥测试结果和需要心脏病学转诊 (p<0.001) 之间发现了显著的关联.
- 该测试被评为易于执行,参与者推率为87.5%.
结论:
- 卡迪西奥测试是一种简单的,临近患者的工具,用于识别潜在的心血管疾病.
- 与传统的12导心电图相比,它可以更好地识别高风险,难以接触的个体中的心血管疾病.
- 这项技术促进了新的护理途径,并解决了健康不平等问题.
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