The Seasonal Fluctuation of Fatigue in Multiple Sclerosis.
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BORIS DOI
Publisher DOI
PubMed ID
35785351
Description
Background
Fatigue is a common symptom in patients with multiple sclerosis. Several studies suggest that outdoor temperature can impact fatigue severity, but a systematic study of seasonal variations is lacking.
Methods
Fatigue was assessed with the Fatigue Scale for Motor and Cognitive Functions (FSMC) in a temperate climatic zone with an average outdoor temperature of 8.8°C. This study included 258 patients with multiple sclerosis from 572 visits temporally distributed over the year. The data were adjusted for age, sex, cognition, depression, disease severity, and follow-up time. Linear regression models were performed to determine whether the temporal course of fatigue was time-independent, linearly time dependent, or non-linearly time dependent.
Results
Fatigue was lowest during January (mean FSMC: 49.84) and highest during August (mean FSMC: 53.88). The regression analysis showed the best fit with a model that included months + months2, which was a non-linear time dependency. Mean FSMC per month correlated significantly with the average monthly temperature (ρ = 0.972; p < 0.001).
Conclusion
In multiple sclerosis, fatigue showed a natural temporal fluctuation. Fatigue was higher during summer compared to winter, with a significant relationship of fatigue with outdoor temperature. This finding should be carefully taken into account when clinically monitoring patients over time to not interpret higher or lower scores independent of seasonal aspects.
Fatigue is a common symptom in patients with multiple sclerosis. Several studies suggest that outdoor temperature can impact fatigue severity, but a systematic study of seasonal variations is lacking.
Methods
Fatigue was assessed with the Fatigue Scale for Motor and Cognitive Functions (FSMC) in a temperate climatic zone with an average outdoor temperature of 8.8°C. This study included 258 patients with multiple sclerosis from 572 visits temporally distributed over the year. The data were adjusted for age, sex, cognition, depression, disease severity, and follow-up time. Linear regression models were performed to determine whether the temporal course of fatigue was time-independent, linearly time dependent, or non-linearly time dependent.
Results
Fatigue was lowest during January (mean FSMC: 49.84) and highest during August (mean FSMC: 53.88). The regression analysis showed the best fit with a model that included months + months2, which was a non-linear time dependency. Mean FSMC per month correlated significantly with the average monthly temperature (ρ = 0.972; p < 0.001).
Conclusion
In multiple sclerosis, fatigue showed a natural temporal fluctuation. Fatigue was higher during summer compared to winter, with a significant relationship of fatigue with outdoor temperature. This finding should be carefully taken into account when clinically monitoring patients over time to not interpret higher or lower scores independent of seasonal aspects.
Date of Publication
2022-06
Publication Type
Article
Subject(s)
Keyword(s)
fatigue multiple sclerosis neuropsychological seasonal sun
Language(s)
en
Contributor(s)
Grothe, Matthias | |
Gross, Stefan | |
Süße, Marie | |
Strauss, Sebastian |
Additional Credits
Series
Frontiers in neurology
Publisher
Frontiers Media S.A.
ISSN
1664-2295
Access(Rights)
open.access