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在多病症测量中高阶疾病相互作用:边际益处超过附加性疾病总和
Melissa Y Wei1,2, Chi-Hong Tseng1, Ashley J Kang1
1Division of General Internal Medicine and Health Services Research, Department of Medicine, University of California, Los Angeles, Los Angeles, California, USA.
将疾病相互作用纳入多病态度指标显示出最小的改善. 一个精确的指数可以结合疾病的影响和它们的显著相互作用,以更好地预测健康结果.
科学领域:
- 老年学是一门学科.
- 流行病学 流行病学
- 生物统计学 生物统计学
背景情况:
- 目前的多病性措施往往通过假设附加效应来过度简化疾病影响.
- 这忽略了在某些疾病组合中观察到的协同效应.
- 高阶疾病相互作用对于准确的健康结果预测至关重要.
研究的目的:
- 将同时发生的更高阶疾病相互作用纳入多病性加权指数.
- 通过包括这些相互作用来评估模型的改进.
- 为了提高多病态度测量的精度.
主要方法:
- 使用健康和退休研究参与者与相关的医疗保险数据 (ICD-9-CM索赔,1991-2012).
- 评估了20个最常见和具有影响力的条件的更高阶相互作用 (2-way,3-way).
- 采用LASSO和引导用于统计学上显著的相互作用识别;与模型相比,与相互作用相匹配和没有相互作用.
主要成果:
- 分析包括了来自18212名参与者的73,830个观察结果.
- 没有相互作用的多发病率加权指数得到R2=0.26.
- 在前10个条件中添加双向相互作用,R2略有改善至0.27;三向相互作用的影响最小.
结论:
- 介绍了用于多病性疾病测量的更高阶疾病相互作用的新见解.
- 结合前10个条件的双向相互作用,可以获得最小的模型适合性改进.
- 一个更精确的多病症指数应该整合主要疾病影响和重大相互作用.
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