Multidimensional predictors of fatigue in amyotrophic lateral sclerosis: a cross-sectional study in China

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Authors: Fangfang Cai, Dandan Xu, Dan Yang, Fei Huang, Xiaoyu Song, Qianping Jiang, ShiLei Wan, Yan Zhao, Jing Zhou
Cited by: 0
References: 19

Abstract

This study aims to identify key predictors of fatigue in patients with amyotrophic lateral sclerosis (ALS) and examine the interaction of physiological, psychological, and social factors to inform management strategies. A descriptive cross-sectional study. Between June 2023 and June 2024, a cohort of 239 patients diagnosed with ALS enrolled at the Integrated Traditional Chinese and Western Medicine Center, Hubei Provincial Hospital of Traditional Chinese Medicine. The participants were evaluated using validated instruments that assessed motor function, depressive symptoms, sleep quality, and social determinants. Stepwise multiple regression analysis was conducted to identify independent predictors of fatigue. The ALS Functional Rating Scale-Revised (ALSFRS-R), depression (PHQ-9), sleep quality (PSQI), and residential status were significant predictors of fatigue, accounting for 28.6% of the variance (R2= 0.286). The use of traditional Chinese medicine was associated with a reduction in fatigue, whereas muscle strength exhibited an inverse correlation with the severity of fatigue. Fatigue in ALS is influenced by multiple factors, extending beyond motor decline to include psychological well-being, sleep quality, and the social environment. These findings highlight the need for multidisciplinary, personalized strategies that integrate both biomedical and supportive care approaches to enhance the quality of life for ALS patients.

Fields of Study & Subjects

Amyotrophic Lateral Sclerosis Research Parkinson's Disease and Spinal Disorders Neurogenetic and Muscular Disorders Research

Publication details

Journal / source
Scientific Reports
Volume
16
Issue
1
Pages
3294–3294
Publication date
1 January 2026
Language
EN