Frailty in older maintenance hemodialysis patients: A latent class analysis revealing personalized management

BACKGROUND: Elderly patients undergoing maintenance hemodialysis (MHD) exhibit an elevated risk of frailty, which is strongly associated with adverse clinical outcomes, including increased mortality. However, current frailty assessment tools often overlook intrinsic patient heterogeneity, limiting their clinical utility. This study employs latent class analysis to identify distinct frailty profiles in elderly MHD patients, aiming to explore heterogeneity in frailty phenotypes and identify associated factors, thereby informing the development of targeted interventions. METHODS: Data were collected from 227 elderly patients receiving MHD in Guangdong Province, China, from January to April 2023. Participants were assessed using a general information questionnaire and the Fried scale. Latent class analysis was applied to identify subgroups based on frailty characteristics, and Firth logistic regression was used to examine factors associated with frailty class membership. RESULTS: Two distinct frailty subgroups were identified: Class 1 (low physical activity-high frailty group, 55.1%) and Class 2 (high physical activity-low frailty group, 44.9%). Firth logistic regression demonstrated that combined hypertension (odds ratio [OR] = 0.023; 95% confidence interval [CI]: 0.002-0.119; P < 0.001), older age (OR = 0.746; 95% CI: 0.618-0.840; P < 0.001), longer dialysis duration (OR = 0.935; 95% CI: 0.874-0.976; P = 0.001), lower serum albumin concentration (OR = 0.884; 95% CI: 0.775-0.973; P = 0.010), and lower serum creatinine concentration (OR = 0.996; 95% CI: 0.992-0.999; P = 0.017) were significantly associated with belonging to the high-frailty group. Overweight showed a trend toward a protective association but did not reach statistical significance (OR = 5.874; 95% CI: 0.900-55.438; P = 0.065). CONCLUSIONS: This study highlights the heterogeneity of frailty among elderly maintenance hemodialysis patients. Combined hypertension was strongly and inversely associated with the low-frailty group, indicating its predominance in the high-frailty phenotype. Older age, longer dialysis duration, lower serum albumin levels, and lower serum creatinine levels were significantly associated with the high-frailty phenotype. These findings underscore the importance of personalized frailty assessment and interventions, such as blood pressure management, nutritional support, and tailored exercise programs, to improve health outcomes in this vulnerable population. Future multicenter longitudinal studies are warranted to validate these frailty phenotypes and evaluate their predictive value for clinical outcomes.

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Journal
PLoS ONE
Published
2026-06-16
DOI
https://doi.org/10.1371/journal.pone.0351155
Primary Topic
Dialysis and Renal Disease Management
Type
article
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article

Frailty in older maintenance hemodialysis patients: A latent class analysis revealing personalized management

Xuemei Xian, Mengxing Wang, Surui Liang, Yi-Xiang Wang et al.
PLoS ONE
Dialysis and Renal Disease Management
article

Frailty in older maintenance hemodialysis patients: A latent class analysis revealing personalized management

Xuemei Xian, Mengxing Wang, Surui Liang, Yi-Xiang Wang, Luyang Jin, Dingyuan Wei, Fangping Chen, Siyi Li, Xingyue Guo, Didi Xu
article en

Abstract

BACKGROUND: Elderly patients undergoing maintenance hemodialysis (MHD) exhibit an elevated risk of frailty, which is strongly associated with adverse clinical outcomes, including increased mortality. However, current frailty assessment tools often overlook intrinsic patient heterogeneity, limiting their clinical utility. This study employs latent class analysis to identify distinct frailty profiles in elderly MHD patients, aiming to explore heterogeneity in frailty phenotypes and identify associated factors, thereby informing the development of targeted interventions. METHODS: Data were collected from 227 elderly patients receiving MHD in Guangdong Province, China, from January to April 2023. Participants were assessed using a general information questionnaire and the Fried scale. Latent class analysis was applied to identify subgroups based on frailty characteristics, and Firth logistic regression was used to examine factors associated with frailty class membership. RESULTS: Two distinct frailty subgroups were identified: Class 1 (low physical activity-high frailty group, 55.1%) and Class 2 (high physical activity-low frailty group, 44.9%). Firth logistic regression demonstrated that combined hypertension (odds ratio [OR] = 0.023; 95% confidence interval [CI]: 0.002-0.119; P < 0.001), older age (OR = 0.746; 95% CI: 0.618-0.840; P < 0.001), longer dialysis duration (OR = 0.935; 95% CI: 0.874-0.976; P = 0.001), lower serum albumin concentration (OR = 0.884; 95% CI: 0.775-0.973; P = 0.010), and lower serum creatinine concentration (OR = 0.996; 95% CI: 0.992-0.999; P = 0.017) were significantly associated with belonging to the high-frailty group. Overweight showed a trend toward a protective association but did not reach statistical significance (OR = 5.874; 95% CI: 0.900-55.438; P = 0.065). CONCLUSIONS: This study highlights the heterogeneity of frailty among elderly maintenance hemodialysis patients. Combined hypertension was strongly and inversely associated with the low-frailty group, indicating its predominance in the high-frailty phenotype. Older age, longer dialysis duration, lower serum albumin levels, and lower serum creatinine levels were significantly associated with the high-frailty phenotype. These findings underscore the importance of personalized frailty assessment and interventions, such as blood pressure management, nutritional support, and tailored exercise programs, to improve health outcomes in this vulnerable population. Future multicenter longitudinal studies are warranted to validate these frailty phenotypes and evaluate their predictive value for clinical outcomes.

PLoS ONEVol. 21(6)
Sir Run Run Shaw Hospital (CN), Memorial Foundation (US), Hangzhou Hospital of Traditional Chinese Medicine (CN), Southern Medical University Shenzhen Hospital (CN), Zhejiang University (CN)
Good health and well-being
Openalex Percentile: Top 7%
Dialysis and Renal Disease Management
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