ArticleScientific reports2023
EDSS and infratentorial white matter lesion volume are considered predictors of fatigue severity in RRMS.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 7 citations in OpenAlex.
- Investigating the Relationship Between Visual Evoked Potentials, Neurological and Neuropsychological Status in Primary Progressive Multiple Sclerosis.Journal of clinical medicine · 2026Article
- Physical Function, Muscle Strength, and Fatigue in Patients with Multiple Sclerosis: An Exploratory Cross-Sectional Study.Journal of functional morphology and kinesiology · 2025Article
- Disability and Non-Motor Symptoms in Multiple Sclerosis: Exploring Associations and Predictive Factors.Brain sciences · 2025Article
- Exploring the dynamics of stability and lumbar proprioception in hypermobility syndrome: a comparative and mediation analysis.Journal of orthopaedic surgery and research · 2025Article
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Fatigue is a common disabling symptom of relapsing remitting multiple sclerosis (RRMS). Many studies have linked grey matter atrophy to fatigue, but white matter lesion load (WM-LL) has received less attention. Here we assess the relation between fatigue and regional WM-LL volumetric measures. 63 patients with RRMS participated in this study; mean age was 31.9 ± 8.1 years. Each patient provided demographic details and was scored on the expanded disability status scale (EDSS) and fatigue severity scale (FSS). VolBrain, a fully automated, operator-independent tool was used to assess WM-LL and whole brain volume. The patients were classified into three groups: no fatigue (FSS < 4), low to moderate fatigue (FSS ≥ 4 ≤ 5) and high fatigue (FSS > 5). 33.3% of patients had no significant fatigue, 25.4% had mild-to-moderate fatigue, and 41.3% had significant fatigue. Age, disease duration, relapses, and EDSS were positively correlated to fatigue severity (P = 0.034, 0.002, 0.009 and 0.001 respectively). Whole brain volume, total and regional WM-LL (juxtacortical, periventricular, infratentorial) were also correlated with fatigue severity. Ordinal regression analysis for fatigue severity showed EDSS and infratentorial lesion volume were the best predictors. In conclusion, EDSS and infratentorial lesion volume (cerebellar and brainstem) are the best predictors of fatigue severity.
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