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Longitudinal correlates of fatigue in multiple sclerosis.
E Patrick1, C Christodoulou, L B Krupp
1Department of Neurology, State University of New York at Stony Brook, New York 11794-8121, USA.
Summary
Predictors of fatigue in multiple sclerosis (MS) include baseline fatigue, pain, and mood. These factors significantly influence fatigue levels over time, aiding in patient management.
Area of Science:
- Neurology
- Clinical Research
- Patient Outcomes
Background:
- Fatigue is the most prevalent symptom in multiple sclerosis (MS).
- Understanding fatigue predictors in MS remains a significant clinical challenge.
- The New York State Multiple Sclerosis Consortium (NYSMSC) database provides extensive longitudinal data for MS research.
Purpose of the Study:
- To identify predictors of longitudinal changes in fatigue.
- To examine the influence of pain, mood, and neurological impairment on MS fatigue.
- To analyze these predictors across different multiple sclerosis subtypes.
Main Methods:
- Utilized baseline and 1-year follow-up data from 2768 patients in the NYMSC database.
- Assessed fatigability, pain, depressive symptoms, MS subtype, and Expanded Disability Status Scale (EDSS).
- Employed correlational and multiple regression analyses to determine fatigue correlates and predictors.
Main Results:
- Baseline fatigue, pain, and depression explained 34.6% of the variance in 1-year follow-up fatigue.
- Fatigue levels were lower in relapsing-remitting MS compared to other subtypes.
- Consistent correlations were observed between fatigue, depressive symptoms, pain severity, and EDSS at baseline and follow-up.
Conclusions:
- Baseline fatigue, pain, mood, and EDSS are significant predictors of 1-year fatigue outcomes.
- These key symptoms demonstrate inter-correlations at baseline, follow-up, and in change scores.
- Identifying fatigue predictors can significantly improve patient management strategies in MS.
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