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Fatigue and progression of corpus callosum atrophy in multiple sclerosis

Overview of attention for article published in Journal of Neurology, May 2011
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Title
Fatigue and progression of corpus callosum atrophy in multiple sclerosis
Published in
Journal of Neurology, May 2011
DOI 10.1007/s00415-011-6091-0
Pubmed ID
Authors

Özgür Yaldizli, Stephanie Glassl, Dietrich Sturm, Athina Papadopoulou, Achim Gass, Barbara Tettenborn, Norman Putzki

Abstract

Fatigue is one of the most disabling symptoms in multiple sclerosis (MS) patients. There is no or only weak correlation between conventional magnetic resonance imaging (MRI) parameters and level of fatigue. The aim of this study was to investigate the relationship between progression of corpus callosum (CC) atrophy and fatigue in MS patients. This was a cohort study in 70 patients with relapsing form of MS (RRMS) and serial MRIs over a mean follow-up of 4.8 years [67% female, mean age 42 ± 11 years, mean disease duration 9.7 ± 7.6 years, mean Expanded Disability Status Scale (EDSS) 2.8 ± 1.6]. Fatigue was assessed by the Fatigue Severity Scale (FSS). CC size was measured with the CC index (CCI). In total, 40% of the patients suffered from fatigue (mean FSS score 5.3 ± 1.1) and 60% patients had no fatigue (mean FSS score of 2.1 ± 1). Patients with fatigue had higher EDSS scores (p = 0.01) and CC atrophy was more pronounced in patients with fatigue (-21.8 vs. -12.1%, p = 0.005). FSS correlated with CCI change over time (r = -0.33; p = 0.009) and EDSS (p = 0.008; r = 0.361). The association between annualized CCI change and FSS was independent from EDSS, disease duration, gender and age in a multivariate linear regression analysis (p < 0.001). Progression of CC atrophy may play a role in the evolution of MS-related fatigue.

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Mendeley readers

The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 1%
Unknown 66 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 18%
Student > Master 8 12%
Professor > Associate Professor 7 10%
Student > Doctoral Student 7 10%
Other 5 7%
Other 15 22%
Unknown 13 19%
Readers by discipline Count As %
Medicine and Dentistry 15 22%
Neuroscience 11 16%
Psychology 9 13%
Agricultural and Biological Sciences 8 12%
Computer Science 2 3%
Other 5 7%
Unknown 17 25%