通过基于算法和公式的脉冲波速度预测心血管事件
Louis-Charles Desbiens1, Simon Veillette1, Catherine Fortier2,3
1Department of Medicine, Université de Montréal, Montreal.
Journal of hypertension
|November 13, 2025
概括
基于算法的脉冲波速度 (PWV) 估计显著提高心血管风险预测超出目前的工具. 基于公式的估计可能缺乏通用性,突出了对动脉硬度评估的算法方法的价值.
科学领域:
- 心脏病学 心脏病学
- 血管生物学 血管生物学
- 预防医学 预防医学
背景情况:
- 带脉脉冲波速率 (PWV) 是动脉硬性的关键指标,也是心血管疾病风险因素.
- 目前用于测量PWV的方法耗时,这促使开发估计技术.
- 估计PWV (ePWV) 在改善超越现有工具的心血管风险预测方面的临床实用性仍然不确定.
研究的目的:
- 评估两种基于公式 (ePWV f) 和基于算法 (ePWV algo) 的ePWV方法在预测主要心血管不良事件 (MACE) 方面的能力.
- 为了确定ePWV是否会改善心血管风险预测,当它被添加到已建立的风险得分,如ASCVD和SCORE-2.
主要方法:
- 利用了基于人口的CARTaGENE队列 (40-69岁) 的数据.
- 使用已发表的公式 (ePWV f) 和算法转换 (ePWV algo) 计算 ePWV.
- 使用ASCVD和SCORE-2方程评估10年MACE风险,然后使用Cox模型分析ePWV和MACE之间的关联,并根据风险得分进行调整.
主要成果:
- 在17548名参与者中,有2263人 (12.9%) 经历了MACE.
- 经过ASCVD (HR=1.16) 和SCORE-2 (HR=1.07) 的调整后,ePWV算法与MACE显著相关.
- 在整体队列中对任何风险得分进行调整后,ePWV f与MACE没有显著关联.
结论:
- 基于算法的ePWV提高了超越传统风险方程的心血管风险预测.
- 基于公式的ePWV的预测性能可能仅限于它衍生出来的特定种群.
- 算法式ePWV为心血管风险评估提供了一个更具普遍性和更有价值的工具.
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