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The Seasonal Fluctuation of Fatigue in Multiple Sclerosis
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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9247309/ https://www.ncbi.nlm.nih.gov/pubmed/35785351 http://dx.doi.org/10.3389/fneur.2022.900792 |
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author | Grothe, Matthias Gross, Stefan Süße, Marie Strauss, Sebastian Penner, Iris Katharina |
author_facet | Grothe, Matthias Gross, Stefan Süße, Marie Strauss, Sebastian Penner, Iris Katharina |
author_sort | Grothe, Matthias |
collection | PubMed |
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 + months(2), 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. |
format | Online Article Text |
id | pubmed-9247309 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92473092022-07-02 The Seasonal Fluctuation of Fatigue in Multiple Sclerosis Grothe, Matthias Gross, Stefan Süße, Marie Strauss, Sebastian Penner, Iris Katharina Front Neurol Neurology 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 + months(2), 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. Frontiers Media S.A. 2022-06-17 /pmc/articles/PMC9247309/ /pubmed/35785351 http://dx.doi.org/10.3389/fneur.2022.900792 Text en Copyright © 2022 Grothe, Gross, Süße, Strauss and Penner. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neurology Grothe, Matthias Gross, Stefan Süße, Marie Strauss, Sebastian Penner, Iris Katharina The Seasonal Fluctuation of Fatigue in Multiple Sclerosis |
title | The Seasonal Fluctuation of Fatigue in Multiple Sclerosis |
title_full | The Seasonal Fluctuation of Fatigue in Multiple Sclerosis |
title_fullStr | The Seasonal Fluctuation of Fatigue in Multiple Sclerosis |
title_full_unstemmed | The Seasonal Fluctuation of Fatigue in Multiple Sclerosis |
title_short | The Seasonal Fluctuation of Fatigue in Multiple Sclerosis |
title_sort | seasonal fluctuation of fatigue in multiple sclerosis |
topic | Neurology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9247309/ https://www.ncbi.nlm.nih.gov/pubmed/35785351 http://dx.doi.org/10.3389/fneur.2022.900792 |
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