电心图变化的算法用于对急性肺血栓栓塞症患者的血栓负担的定量和局部分析
Fan Wang1, Lan Wang2, ChunXi Yan3
1Department of Cardiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, 200072 Shanghai, China.
Reviews in cardiovascular medicine
|July 30, 2024
概括
新的CHARIS算法可以使用心电图 (ECG) 发现来评估肺血栓栓塞 (PTE) 凝块负担. 这些模型提供定量和局部分析,有助于早期识别严重的PTE病例.
科学领域:
- 心脏病学 心脏病学
- 肺部医学 肺部医学
- 医疗成像医学成像
背景情况:
- 心电图 (ECG) 异常与肺血栓塞栓症 (PTE) 严重程度相关.
- 之前的研究还没有彻底研究单独使用心电图发现来评估中国患者的PTE血栓负担.
- 这项研究旨在开发基于ECG的新型模型,用于对急性PTE中凝块负担的定量和局部分析.
研究的目的:
- 建立和验证使用心电图信号的新型风险预测模型,用于在急性PTE患者中对凝块负担的定量和局部分析.
- 在成像诊断之前评估心电图发现在识别患有重型血栓负担的患者中的有用性.
主要方法:
- 在3个中心 (2015-2019) 的341名急性PTE患者进行了一项回顾性队列研究.
- 在入院时对12导电心电图和计算机断层扫描肺血管造影 (CTPA) 功能进行分析,以确定Qanadli分数.
- 开发和验证CHARIS I和CHARIS II风险预测模型,使用导出和外部验证队列.
主要成果:
- 在CHARIS I模型中,以适度的歧视量化评估了Qanadli分数 (C指数0.720在导出中,0.663在验证中).
- 该CHARIS II模型预测了类似歧视的干阻塞概率 (导出时的c指数为0.753,验证时为0.741).
- 校准曲线和决策曲线分析证实了CHARIS算法的准确性和临床实用性.
结论:
- CHARIS算法提供了对急性PTE患者的凝块负担的定量和局部洞察.
- 这些基于心电图的模型可以在成像确认之前识别重型血栓负担的患者.
- 查里斯算法显示了急性PTE早期风险分层的潜力.
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