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The clinical and paraclinical correlates of employment status in multiple sclerosis
B. Srpova, L. Sobisek, K. Novotna, T. Uher, L. Friedova, M. Vaneckova, J. Krasensky, E. Kubala Havrdova, D. Horakova
Jazyk angličtina Země Itálie
Typ dokumentu časopisecké články
NLK
ProQuest Central
od 2000-01-01 do Před 1 rokem
Medline Complete (EBSCOhost)
od 2000-02-01 do Před 1 rokem
Health & Medicine (ProQuest)
od 2000-01-01 do Před 1 rokem
Family Health Database (ProQuest)
od 2000-01-01 do Před 1 rokem
Psychology Database (ProQuest)
od 2000-01-01 do Před 1 rokem
- MeSH
- lidé MeSH
- magnetická rezonanční tomografie MeSH
- neuropsychologické testy MeSH
- posuzování pracovní neschopnosti MeSH
- průřezové studie MeSH
- roztroušená skleróza * komplikace MeSH
- zaměstnanost MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
PURPOSE: To identify the clinical and paraclinical markers of employment status in multiple sclerosis (MS). METHODS: This was a cross-sectional sub-study investigating 1226 MS patients. To minimalized confounding effect, two groups of patients, matched by sex, age, and education, were selected: 307 patients with full time employment and 153 unemployed patients receiving disability pension. We explored associations between employment status and Expanded Disability Status Scale (EDSS), 25 Foot Walk Test (25FWT), Nine Hole Peg Test (9HPT), Brief International Cognitive Assessment for MS (BICAMS), Paced Auditory Serial Addition Test (PASAT), Beck Depression Inventory (BDI), SLOAN charts (SLOAN), and brain volumetric MRI measures. RESULTS: Both groups differed significantly on all variables of interest (p < 0.001). In the univariate analyses, EDSS, SDMT (Symbol Digit Modalities Test) adjusted for BDI, 25FWT, and 9HPT best explained variability in vocational status. In multivariate analyses, the combination of EDSS, 25FWT, SDMT, BDI, and corpus callosum fraction (CCF) explained the greatest variability. As a next step, after patients were matched by EDSS, differences in SDMT, 25FWT (both p < 0.001), 9HPT, CCF, and T2 lesion volume were still present (all p < 0.005) between both groups. The best multivariate model consisted of SDMT, BDI, and T2 lesion volume. CONCLUSIONS: EDSS, walking ability, cognitive performance, and MRI volumetric parameters are independently associated with employment status.
Citace poskytuje Crossref.org
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- $a Srpová, Barbora $u Department of Neurology and Center of Clinical Neuroscience, General University Hospital and First Faculty of Medicine, Charles University, Prague, Czech Republic. barbora.srpova@vfn.cz $1 https://orcid.org/0000000280926625 $7 xx0321726
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- $a PURPOSE: To identify the clinical and paraclinical markers of employment status in multiple sclerosis (MS). METHODS: This was a cross-sectional sub-study investigating 1226 MS patients. To minimalized confounding effect, two groups of patients, matched by sex, age, and education, were selected: 307 patients with full time employment and 153 unemployed patients receiving disability pension. We explored associations between employment status and Expanded Disability Status Scale (EDSS), 25 Foot Walk Test (25FWT), Nine Hole Peg Test (9HPT), Brief International Cognitive Assessment for MS (BICAMS), Paced Auditory Serial Addition Test (PASAT), Beck Depression Inventory (BDI), SLOAN charts (SLOAN), and brain volumetric MRI measures. RESULTS: Both groups differed significantly on all variables of interest (p < 0.001). In the univariate analyses, EDSS, SDMT (Symbol Digit Modalities Test) adjusted for BDI, 25FWT, and 9HPT best explained variability in vocational status. In multivariate analyses, the combination of EDSS, 25FWT, SDMT, BDI, and corpus callosum fraction (CCF) explained the greatest variability. As a next step, after patients were matched by EDSS, differences in SDMT, 25FWT (both p < 0.001), 9HPT, CCF, and T2 lesion volume were still present (all p < 0.005) between both groups. The best multivariate model consisted of SDMT, BDI, and T2 lesion volume. CONCLUSIONS: EDSS, walking ability, cognitive performance, and MRI volumetric parameters are independently associated with employment status.
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- $a Sobisek, Lukas $u Department of Statistics and Probability, University of Economics in Prague, Prague, Czech Republic
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