Comparison of Claims-Based Frailty Indices in U.S. Veterans 65 and Older for Prediction of Long-Term Institutionalization and Mortality.

IF 4.3 2区 医学 Q1 GERIATRICS & GERONTOLOGY
Ariela R Orkaby, Tianwen Huan, Orna Intrator, Shubing Cai, Andrea W Schwartz, Darryl Wieland, Daniel E Hall, Jose F Figueroa, Jordan B Strom, Dae H Kim, Jane A Driver, Bruce Kinosian
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引用次数: 0

Abstract

Background: Frailty is increasingly recognized as a useful measure of vulnerability in older adults. Multiple claims-based frailty indices (CFIs) can readily identify individuals with frailty, but whether 1 CFI improves prediction over another is unknown. We sought to assess the ability of 5 distinct CFIs to predict long-term institutionalization (LTI) and mortality in older Veterans.

Methods: Retrospective study conducted in U.S. Veterans ≥65 years without prior LTI or hospice use in 2014. Five CFIs were compared: Kim, Orkaby (Veteran Affairs Frailty Index [VAFI]), Segal, Figueroa, and the JEN-FI, grounded in different theories of frailty: Rockwood cumulative deficit (Kim and VAFI), Fried physical phenotype (Segal), or expert opinion (Figueroa and JFI). The prevalence of frailty according to each CFI was compared. CFI performance for the coprimary outcomes of any LTI or mortality from 2015 to 2017 was examined. Because Segal and Kim include age, sex, or prior utilization, these variables were added to regression models to compare all 5 CFIs. Logistic regression was used to calculate model discrimination and calibration for both outcomes.

Results: A total of 3 million Veterans were included (mean age 75, 98% male participants, 80% White, and 9% Black). Frailty was identified for between 6.8% and 25.7% of the cohort with 2.6% identified as frail by all 5 CFIs. There was no meaningful difference between CFIs in the area under the receiver operating characteristic curve for LTI (0.78-0.80) or mortality (0.77-0.79).

Conclusions: Based on different frailty constructs, and identifying different subsets of the population, all 5 CFIs similarly predicted LTI or death, suggesting each could be used for prediction or analytics.

美国65岁及以上退伍军人基于索赔的脆弱指数预测长期制度化和死亡率的比较。
背景:脆弱性越来越被认为是衡量老年人脆弱性的有用指标。多个基于索赔的虚弱指数(CFI)可以很容易地识别出有虚弱的个体,但一个CFI是否比另一个更能提高预测能力尚不清楚。我们试图评估5种不同的CFI预测老年退伍军人长期住院治疗(LTI)和死亡率的能力。方法:2014年在美国≥65岁且既往未使用LTI或临终关怀的退伍军人中进行的回顾性研究。比较了五种CFI:Kim、Orkaby(退伍军人事务脆弱指数[VAFI])、Segal、Figueroa和JEN-FI,基于不同的脆弱理论:Rockwood累积缺陷(Kim和VAFI)、Fried身体表型(Segal)或专家意见(Figueroa和JFI)。比较了每个CFI的虚弱患病率。检查了2015年至2017年任何LTI或死亡率的共同主要结果的CFI表现。由于Segal和Kim包括年龄、性别或先前的利用率,因此将这些变量添加到回归模型中,以比较所有5个CFI。逻辑回归用于计算两种结果的模型判别和校准。结果:共有300万退伍军人参与其中(平均年龄75岁,98%为男性,80%为白人,9%为黑人)。在队列中,6.8%-25.7%的人被确定为虚弱,其中2.6%的人被所有5个CFI确定为虚弱。LTI(0.78-0.80)或死亡率(0.77-0.79)受试者操作特征曲线下区域的CFI之间没有显著差异。结论:基于不同的虚弱结构,并识别不同的人群亚群,所有5个CFI都可以类似地预测LTI或死亡,这表明每个CFI都可用于预测或分析。
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来源期刊
CiteScore
10.00
自引率
5.90%
发文量
233
审稿时长
3-8 weeks
期刊介绍: Publishes articles representing the full range of medical sciences pertaining to aging. Appropriate areas include, but are not limited to, basic medical science, clinical epidemiology, clinical research, and health services research for professions such as medicine, dentistry, allied health sciences, and nursing. It publishes articles on research pertinent to human biology and disease.
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