Development and Validation of a Nomogram to Predict Frailty Progression in Nonfrail Chinese Community-Living Older Adults

列线图 医学 逻辑回归 老年学 心理干预 多元统计 婚姻状况 多元分析 物理疗法 人口 统计 内科学 精神科 数学 环境卫生
作者
Bing-Ru Dong,Xiaoqing Gu,Haiying Chen,Jie Gu,Zhigang Pan
出处
期刊:Journal of the American Medical Directors Association [Elsevier]
卷期号:22 (12): 2571-2578.e4 被引量:7
标识
DOI:10.1016/j.jamda.2021.05.020
摘要

Frailty state progression is common among older adults, so it is necessary to identify predictors to implement individualized interventions. We aimed to develop and validate a nomogram to predict frailty progression in community-living older adults.Prospective cohort study.A total of 3170 Chinese community-living people aged ≥60 years were randomly assigned to a training set or validation set at a ratio of 6:4.Candidate predictors (demographic, lifestyle, and medical characteristics) were used to predict frailty state progression as measured with the Fried frailty phenotype at a 4-year follow-up, and multivariate logistic regression analysis was conducted to develop a nomogram, which was validated internally with 1000 bootstrap resamples and externally with the use of a validation set. The C index and calibration plot were used to assess discrimination and calibration of the nomogram, respectively.After a follow-up period of 4 years, 64.1% (917/1430) of the participants in the robust group and 26.0% (453/1740) in the prefrail group experienced frailty progression, which included 9.1% and 21.0%, respectively, who progressed to frailty. Predictors in the final nomogram were age, marital status, physical exercise, baseline frailty state, and diabetes. Based on this nomogram, an online calculator was also developed for easy use. The discriminative ability was good in the training set (C index = 0.861) and was validated using both the internal bootstrap method (C index = 0.861) and an external validation set (C index = 0.853). The calibration plots showed good agreement in both the training and validation sets.An easy-to-use nomogram was developed with good apparent performance using 5 readily available variables to help physicians and public health practitioners to identify older adults at high risk for frailty progression and implement medical interventions.
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