Jiacheng Yang, Yijiang Ouyang, Wenya Zhang, Xinming Tang, Jiahao Xu, Haoqi Zou, Wenyuan Jing, Xiuping He, Ya Yang, Kechun Che, Jiayan Deng, Congcong Pan, Jiaqi He, Mingjuan Yin, Jun Wu, Jindong Ni
{"title":"预测全因死亡率的衰弱评估方法的比较研究:来自NHANES的见解。","authors":"Jiacheng Yang, Yijiang Ouyang, Wenya Zhang, Xinming Tang, Jiahao Xu, Haoqi Zou, Wenyuan Jing, Xiuping He, Ya Yang, Kechun Che, Jiayan Deng, Congcong Pan, Jiaqi He, Mingjuan Yin, Jun Wu, Jindong Ni","doi":"10.1016/j.jamda.2024.105464","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>The 3 most frequently utilized frailty assessment measures are the Fried criteria, FRAIL scale, and Frailty Index (FI). This study aimed to compare predictive capabilities of these 3 measures regarding all-cause mortality in the United States and to identify the key predictive variables.</p><p><strong>Design: </strong>Cross-sectional study.</p><p><strong>Setting and participants: </strong>From the National Health and Nutrition Examination Survey (NHANES) 2005-2018 cycles, a total of 39,631 participants aged 20 and older were included.</p><p><strong>Methods: </strong>Fried status, FRAIL status, and FI status were determined for each individual based on the cutoff values from the continuous scores of their respective scales. Univariate and multivariate models, incorporating 11 covariates-sex, age, body mass index, ethnicity, education, marital status, smoking status, alcohol intake, employment status, poverty-to-income ratio, and total energy intake-were fitted using Cox proportional hazards and 2 machine learning models. Model performance was assessed through Integrated Brier Score (IBS), concordance index (C-index), and area under the curve (AUC) values from 10-fold cross-validation. Key variable analysis was performed using permutation importance and C-index increment. Subgroup analysis was developed according to age.</p><p><strong>Results: </strong>In univariate analyses, FI consistently outperformed Fried and FRAIL, showing significantly lower IBS, and higher C-index and AUC values. In multivariate analyses, few significant differences were found. Permutation importance analysis identified age as the most important variable, followed by Fried status and FI status. Similarly, in C-index increment analysis, age was the top one variable. Subgroup analyses showed that FI status consistently performed best in all metrics across univariate analyses at least in 40-59 and 60-79 age groups. FI status consistently emerged as the most important variable in permutation analysis across all age groups.</p><p><strong>Conclusions and implications: </strong>FI demonstrated the best performance as a single predictor in predicting all-cause mortality, with age being crucial for enhancing predictive performance. Future research should explore the applicability of FI in different populations and its relationship with cause-specific mortality.</p>","PeriodicalId":17180,"journal":{"name":"Journal of the American Medical Directors Association","volume":" ","pages":"105464"},"PeriodicalIF":4.2000,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparative Study of Frailty Assessment Measures in Predicting All-Cause Mortality: Insights From NHANES.\",\"authors\":\"Jiacheng Yang, Yijiang Ouyang, Wenya Zhang, Xinming Tang, Jiahao Xu, Haoqi Zou, Wenyuan Jing, Xiuping He, Ya Yang, Kechun Che, Jiayan Deng, Congcong Pan, Jiaqi He, Mingjuan Yin, Jun Wu, Jindong Ni\",\"doi\":\"10.1016/j.jamda.2024.105464\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objectives: </strong>The 3 most frequently utilized frailty assessment measures are the Fried criteria, FRAIL scale, and Frailty Index (FI). This study aimed to compare predictive capabilities of these 3 measures regarding all-cause mortality in the United States and to identify the key predictive variables.</p><p><strong>Design: </strong>Cross-sectional study.</p><p><strong>Setting and participants: </strong>From the National Health and Nutrition Examination Survey (NHANES) 2005-2018 cycles, a total of 39,631 participants aged 20 and older were included.</p><p><strong>Methods: </strong>Fried status, FRAIL status, and FI status were determined for each individual based on the cutoff values from the continuous scores of their respective scales. Univariate and multivariate models, incorporating 11 covariates-sex, age, body mass index, ethnicity, education, marital status, smoking status, alcohol intake, employment status, poverty-to-income ratio, and total energy intake-were fitted using Cox proportional hazards and 2 machine learning models. Model performance was assessed through Integrated Brier Score (IBS), concordance index (C-index), and area under the curve (AUC) values from 10-fold cross-validation. Key variable analysis was performed using permutation importance and C-index increment. Subgroup analysis was developed according to age.</p><p><strong>Results: </strong>In univariate analyses, FI consistently outperformed Fried and FRAIL, showing significantly lower IBS, and higher C-index and AUC values. In multivariate analyses, few significant differences were found. Permutation importance analysis identified age as the most important variable, followed by Fried status and FI status. Similarly, in C-index increment analysis, age was the top one variable. Subgroup analyses showed that FI status consistently performed best in all metrics across univariate analyses at least in 40-59 and 60-79 age groups. 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Comparative Study of Frailty Assessment Measures in Predicting All-Cause Mortality: Insights From NHANES.
Objectives: The 3 most frequently utilized frailty assessment measures are the Fried criteria, FRAIL scale, and Frailty Index (FI). This study aimed to compare predictive capabilities of these 3 measures regarding all-cause mortality in the United States and to identify the key predictive variables.
Design: Cross-sectional study.
Setting and participants: From the National Health and Nutrition Examination Survey (NHANES) 2005-2018 cycles, a total of 39,631 participants aged 20 and older were included.
Methods: Fried status, FRAIL status, and FI status were determined for each individual based on the cutoff values from the continuous scores of their respective scales. Univariate and multivariate models, incorporating 11 covariates-sex, age, body mass index, ethnicity, education, marital status, smoking status, alcohol intake, employment status, poverty-to-income ratio, and total energy intake-were fitted using Cox proportional hazards and 2 machine learning models. Model performance was assessed through Integrated Brier Score (IBS), concordance index (C-index), and area under the curve (AUC) values from 10-fold cross-validation. Key variable analysis was performed using permutation importance and C-index increment. Subgroup analysis was developed according to age.
Results: In univariate analyses, FI consistently outperformed Fried and FRAIL, showing significantly lower IBS, and higher C-index and AUC values. In multivariate analyses, few significant differences were found. Permutation importance analysis identified age as the most important variable, followed by Fried status and FI status. Similarly, in C-index increment analysis, age was the top one variable. Subgroup analyses showed that FI status consistently performed best in all metrics across univariate analyses at least in 40-59 and 60-79 age groups. FI status consistently emerged as the most important variable in permutation analysis across all age groups.
Conclusions and implications: FI demonstrated the best performance as a single predictor in predicting all-cause mortality, with age being crucial for enhancing predictive performance. Future research should explore the applicability of FI in different populations and its relationship with cause-specific mortality.
期刊介绍:
JAMDA, the official journal of AMDA - The Society for Post-Acute and Long-Term Care Medicine, is a leading peer-reviewed publication that offers practical information and research geared towards healthcare professionals in the post-acute and long-term care fields. It is also a valuable resource for policy-makers, organizational leaders, educators, and advocates.
The journal provides essential information for various healthcare professionals such as medical directors, attending physicians, nurses, consultant pharmacists, geriatric psychiatrists, nurse practitioners, physician assistants, physical and occupational therapists, social workers, and others involved in providing, overseeing, and promoting quality