新的CAC分散和密度得分可以预测心肌梗塞和心血管死亡率
Gavin Huangfu1,2,3, Abdul R Ihdayhid1,3,4, Simon Kwok5
1Department of Cardiology, Fiona Stanley Hospital, Perth, WA, Australia (G.H., A.R.I., H.S., L.D., G.D.).
Circulation. Cardiovascular imaging
|July 4, 2025
概括
与传统的阿加斯顿分数 (AS) 相比,新的冠状动脉化-分散和密度 (CAC-DAD) 评分可以更好地预测主要不良心血管事件 (MACE). 这种新的得分可以识别高风险患者,即使是低AS患者,也需要加强预防疗法.
科学领域:
- 心脏病学 心脏病学
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 冠状动脉化 (CAC) 是主要不良心血管事件 (MACE) 的强有力的预测因素.
- 目前的方法,如阿加斯顿分数 (AS),不考虑斑块分布或密度.
- 一个新的冠状动脉化-分散和密度 (CAC-DAD) 评分旨在通过考虑这些因素来提高预后价值.
研究的目的:
- 调查新型CAC-DAD评分是否为MACE预测提供了优越的预后价值,而不是传统的AS.
- 评估斑块分布和高密度化对心血管风险评估的影响.
主要方法:
- 一项多中心的回顾性研究包括961名接受心脏计算机断层扫描的患者.
- 使用深度学习算法计算CAC-DAD分数,并结合斑块的空间分布和密度 (≥1000 HU).
- 虚弱回归分析评估了CAC得分和MACE在30天的中位随访期间之间的关联.
主要成果:
- 在CAC-DAD得分 (≥2050) 中,发现的MACE (74%) 比AS (≥400) (57%;P=0.002) 多 (57%;P=0.002).
- 多变量分析证实了CAC-DAD得分 (HR,2.57;P=0.002),年龄,他类药物和糖尿病作为重要的MACE预测因素.
- 将CAC-DAD纳入AS和人口统计学模型,使C统计从0.61提高到0.66 (P=0.008).
结论:
- 自动化的CAC-DAD评分可以提高MACE预测,超出传统的AS.
- 患有高CAC-DAD分数的患者,即使是低AS患者,也可能需要加强预防性心血管治疗.
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