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EDSS and infratentorial white matter lesion volume are considered predictors of fatigue severity in RRMS

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 pa...

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Autores principales: Ezzeldin, Mohammed Y., Mahmoud, Doaa M., Safwat, Shady M., Soliman, Radwa Kamel, Desoky, Tarek, Khedr, Eman M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10349096/
https://www.ncbi.nlm.nih.gov/pubmed/37452063
http://dx.doi.org/10.1038/s41598-023-38368-3
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author Ezzeldin, Mohammed Y.
Mahmoud, Doaa M.
Safwat, Shady M.
Soliman, Radwa Kamel
Desoky, Tarek
Khedr, Eman M.
author_facet Ezzeldin, Mohammed Y.
Mahmoud, Doaa M.
Safwat, Shady M.
Soliman, Radwa Kamel
Desoky, Tarek
Khedr, Eman M.
author_sort Ezzeldin, Mohammed Y.
collection PubMed
description 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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spelling pubmed-103490962023-07-16 EDSS and infratentorial white matter lesion volume are considered predictors of fatigue severity in RRMS Ezzeldin, Mohammed Y. Mahmoud, Doaa M. Safwat, Shady M. Soliman, Radwa Kamel Desoky, Tarek Khedr, Eman M. Sci Rep Article 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. Nature Publishing Group UK 2023-07-14 /pmc/articles/PMC10349096/ /pubmed/37452063 http://dx.doi.org/10.1038/s41598-023-38368-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Ezzeldin, Mohammed Y.
Mahmoud, Doaa M.
Safwat, Shady M.
Soliman, Radwa Kamel
Desoky, Tarek
Khedr, Eman M.
EDSS and infratentorial white matter lesion volume are considered predictors of fatigue severity in RRMS
title EDSS and infratentorial white matter lesion volume are considered predictors of fatigue severity in RRMS
title_full EDSS and infratentorial white matter lesion volume are considered predictors of fatigue severity in RRMS
title_fullStr EDSS and infratentorial white matter lesion volume are considered predictors of fatigue severity in RRMS
title_full_unstemmed EDSS and infratentorial white matter lesion volume are considered predictors of fatigue severity in RRMS
title_short EDSS and infratentorial white matter lesion volume are considered predictors of fatigue severity in RRMS
title_sort edss and infratentorial white matter lesion volume are considered predictors of fatigue severity in rrms
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10349096/
https://www.ncbi.nlm.nih.gov/pubmed/37452063
http://dx.doi.org/10.1038/s41598-023-38368-3
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