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如何通过 10 个步骤从现有数据集构建衰弱指数。

How to construct a frailty index from an existing dataset in 10 steps.

机构信息

School of Physiotherapy, Dalhousie University, Halifax, NS, B3H 4R2, Canada.

Geriatric Medicine, Dalhousie University, Halifax, NS, B3H 2E1, Canada.

出版信息

Age Ageing. 2023 Dec 1;52(12). doi: 10.1093/ageing/afad221.

Abstract

BACKGROUND

The frailty index is commonly used in research and clinical practice to quantify health. Using a health deficit accumulation model, a frailty index can be calculated retrospectively from data collected via survey, interview, performance test, laboratory report, clinical or administrative medical record, or any combination of these. Here, we offer a detailed 10-step approach to frailty index creation, with a worked example.

METHODS

We identified 10 steps to guide the creation of a valid and reliable frailty index. We then used data from waves 5 to 12 of the Health and Retirement Study (HRS) to illustrate the steps.

RESULTS

The 10 steps are as follows: (1) select every variable that measures a health problem; (2) exclude variables with more than 5% missing values; (3) recode the responses to 0 (no deficit) through 1 (deficit); (4) exclude variables when coded deficits are too rare (< 1%) or too common (> 80%); (5) screen the variables for association with age; (6) screen the variables for correlation with each other; (7) count the variables retained; (8) calculate the frailty index scores; (9) test the characteristics of the frailty index; (10) use the frailty index in analyses. In our worked example, we created a 61-item frailty index following these 10 steps.

CONCLUSIONS

This 10-step procedure can be used as a template to create one continuous health variable. The resulting high-information variable is suitable for use as an exposure, predictor or control variable, or an outcome measure of overall health and ageing.

摘要

背景

衰弱指数常用于研究和临床实践中,以量化健康状况。使用健康缺陷累积模型,可以根据通过调查、访谈、表现测试、实验室报告、临床或行政医疗记录收集的数据,或这些数据的任意组合,回顾性地计算衰弱指数。在这里,我们提供了一个详细的 10 步流程来创建衰弱指数,并提供了一个示例。

方法

我们确定了 10 个步骤来指导有效和可靠的衰弱指数的创建。然后,我们使用健康与退休研究(HRS)第 5 至 12 波的数据来说明这些步骤。

结果

这 10 个步骤如下:(1)选择每个测量健康问题的变量;(2)排除缺失值超过 5%的变量;(3)将反应重新编码为 0(无缺陷)至 1(缺陷);(4)当编码缺陷太少(<1%)或太多(>80%)时排除变量;(5)筛选与年龄相关的变量;(6)筛选与其他变量相关的变量;(7)统计保留的变量数;(8)计算衰弱指数得分;(9)测试衰弱指数的特征;(10)在分析中使用衰弱指数。在我们的示例中,我们按照这 10 个步骤创建了一个 61 项的衰弱指数。

结论

此 10 步程序可用作创建单一连续健康变量的模板。由此产生的高信息量变量适用于作为暴露、预测或控制变量,或作为整体健康和衰老的结果衡量指标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b995/10733590/fcd9f7ba29ff/afad221f1.jpg

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