对研究中风预测因子的不同视角:在2型糖尿病患者队列中的纵向和时间到事件数据的联合模型
F J San Andrés-Rebollo1,2,3, J Cárdenas-Valladolid2,3,4, J C Abanades-Herranz2,5
1Las Calesas Health Centre, Madrid, Spain.
Cardiovascular diabetology
|April 16, 2025
概括
联合模型可以改善2型糖尿病中风预测. 关键因素包括年龄,心房动,血压和功能,动态更新可以提高预后准确性.
科学领域:
- 心血管疾病的研究研究.
- 生物统计学 生物统计学
- 糖尿病管理 糖尿病管理
背景情况:
- 传统的预测模型同时评估风险因素和结果,无法捕捉疾病的进展.
- 联合模型将纵向数据与生存分析相结合,以进行动态预后调整.
- 优化中风/暂时性缺血性发作 (TIA) 预测需要结合不断变化的患者数据.
研究的目的:
- 开发和验证用于预测2型糖尿病患者中风或TIA的联合模型.
- 为了更准确的个人预后,动态纳入预测变量的变化.
- 用联合建模评估中风/TIA预测的性别特异性.
主要方法:
- 利用3442名T2DM患者的12年随访,没有先前的心血管事件.
- 采用比例危险和线性混合效应模型,组合成一个联合模型.
- 使用偏差信息标准优化模型选择,并通过曲线下的面积 (AUC) 评估区分能力.
主要成果:
- 303名患者 (8.8%) 在随访期间发生中风/TIA.
- 男人模型包括心房动 (AF),静脉血压 (SBP),腹静脉血压 (DBP),白色素尿和膜过率 (GFR).
- 女性模型包括AF,血压 (BP),功能,HbA1c和LDL胆固醇;AUC>0.70两者.
结论:
- 年龄,AF和SBP在两性中都是显著的预测因素;女性的功能是显著的.
- 在这个队列中,增加的透静血压 (DBP) 显示出保护作用.
- 这些预测因素在研究期间的最后3至7年中最为重要.
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