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Updated: Jul 25, 2025

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
[对老年人心血管疾病风险预测模型的审查]
1Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China.
老年人心血管疾病 (CVD) 风险模型显示出各种结果和高偏差. 外部验证对于改进这些基本的初级预防工具至关重要.
科学领域:
- 老年学是一门学科.
- 心血管医学 心血管医学
- 生物统计学 生物统计学
背景情况:
- 风险预测模型对于老年人群中心血管疾病 (CVD) 的初级预防至关重要.
- 现有的老年人心血管疾病风险预测模型往往缺乏方法严谨性和外部验证.
研究的目的:
- 审查和评估为老年人开发的CVD风险预测模型的质量.
- 确定局限性,并为未来的模型开发提出改进建议.
主要方法:
- 对15项关于老年人心血管疾病风险预测模型的国内和国际研究进行系统审查.
- 评估研究方法,偏差风险,内部验证和外部验证.
主要成果:
- 跨模型的疾病结果定义中存在显著的异质性.
- 十个模型没有足够的方法细节,十个模型有偏差的高风险.
- 13个模型显示中度内部歧视,但只有4个经过外部验证.
- 针对老年人的模型在算法和预测效应方面与一般人口模型不同,性能减弱.
结论:
- 目前的老年人心血管疾病风险预测模型在质量和验证方面存在局限性.
- 高质量的外部验证研究是必不可少的.
- 未来的研究应该探索新的算法,预测器和机器学习等方法来优化这些模型.
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