Geriatric nursing (New York, N.Y.) · 2026
Analysis of latent classes and influencing factors of intrinsic capacity among elderly patients receiving maintenance hemodialysis.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Du Xiaolong, Gao Huanling, Jia Kaixing, Chen Weijing, Ren Xiaojing, Shi Yanwei
Аннотация
OBJECTIVE: To explore the latent classes and influencing factors of intrinsic capacity (IC) among elderly patients undergoing maintenance hemodialysis (MHD).
METHODS: From January 2025 to May 2025, a convenience sampling method was used to recruit elderly MHD patients from two tertiary hospital hemodialysis centers in Shanxi Province. Data were collected using the General Information Questionnaire, General Self-Efficacy Scale, Social Support Rating Scale, eHealth Literacy Scale, and Intrinsic Capacity Assessment Scale. Latent class analysis (LCA) was performed using Mplus 8.3, while chi-square tests and multivariate logistic regression analysis were conducted with SPSS 29.0.
RESULTS: A total of 307 elderly MHD patients were included, and LCA revealed three latent classes of IC: high motor-medium psychological group, low motor-low sensoryhigh psychological group and relatively low group. Multivariate logistic regression analysis identified age, Education background, BMI, personal monthly income, hs-CRP levels, parathyroid hormone, and hemoglobin as significant predictors of IC latent class membership (all P < 0.05).
CONCLUSION: Elderly MHD patients exhibit a high IC impairment rate with marked heterogeneity, influenced by multifaceted factors. Healthcare providers should tailor interventions to specific IC profiles to delay functional decline and promote healthy aging in this population.
METHODS: From January 2025 to May 2025, a convenience sampling method was used to recruit elderly MHD patients from two tertiary hospital hemodialysis centers in Shanxi Province. Data were collected using the General Information Questionnaire, General Self-Efficacy Scale, Social Support Rating Scale, eHealth Literacy Scale, and Intrinsic Capacity Assessment Scale. Latent class analysis (LCA) was performed using Mplus 8.3, while chi-square tests and multivariate logistic regression analysis were conducted with SPSS 29.0.
RESULTS: A total of 307 elderly MHD patients were included, and LCA revealed three latent classes of IC: high motor-medium psychological group, low motor-low sensoryhigh psychological group and relatively low group. Multivariate logistic regression analysis identified age, Education background, BMI, personal monthly income, hs-CRP levels, parathyroid hormone, and hemoglobin as significant predictors of IC latent class membership (all P < 0.05).
CONCLUSION: Elderly MHD patients exhibit a high IC impairment rate with marked heterogeneity, influenced by multifaceted factors. Healthcare providers should tailor interventions to specific IC profiles to delay functional decline and promote healthy aging in this population.