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脂蛋白 (a) 动脉样硬化心血管疾病风险评分发展和预测从现实世界数据的初级预防

Wenjun Fan^1,2, Chuyue Wu³, Nathan D Wong^1,2,3

¹Mary and Steve Wen Cardiovascular Division, Department of Medicine (W.F., N.D.W.), University of California, Irvine.

Circulation. Genomic and precision medicine

|January 24, 2025

概括

开发基于电子健康记录 (EHR) 的算法,其中包括脂蛋白[Lp]改善了动脉样硬化心血管疾病 (ASCVD) 风险预测. 这种新的工具可以识别需要加强ASCVD预防工作的患者.

科学领域:

心脏病学心脏病学
预防医学预防医学
生物标志物生物标志物

背景情况:

脂蛋白 (Lp) 是已知的动脉样硬化心血管疾病 (ASCVD) 的预测因子.
现有的风险预测算法往往缺乏Lp(a) 集成,特别是那些来自现实世界临床数据的算法.
需要改进的ASCVD风险分层工具,包括Lp(a).

研究的目的:

开发和验证基于电子健康记录 (EHR) 的风险预测算法,该算法包含Lp (a) 级别.
评估新算法在识别有ASCVD事件风险的个人的表现.
评估Lp (a) 纳入对风险重新分类的影响,特别是在边界-中间风险人群中.

主要方法:

为了开发风险预测模型,我们使用了一个大型的EHR数据库.
Lp (a) 水平被分类为切割点 (25,50,75 mg/dL).
该模型被外部验证,使用来自美国四项前性研究的聚合队列,并评估了净重新分类改进.

主要成果:

在EHR模型中,除了传统的风险因素外,还纳入了Lp (a).
较高的Lp(a) 水平与ASCVD风险增加显著相关 (例如,Lp(a) ≥75 mg/dL与88%更高的ASCVD风险相关).
包括Lp (a) 改善了C统计数据,并在边界/中间风险患者中显示出21.3%的净重新分类改善.

结论:

从现实世界EHR数据中开发一个增强的ASCVD风险预测模型是可行的.
将Lp(a) 纳入ASCVD预测模型可以显著重新分类患者的风险.
这种改进的风险评估可以为处于风险的个人指导更密集的预防策略.

关键词:

心血管疾病心血管疾病电子健康记录是电子健康记录.脂蛋白 (a) 是一种蛋白质风险评估风险评估风险评估

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