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Predictors of unemployment status in people with relapsing multiple sclerosis: a single center experience.
- Source :
-
Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology [Neurol Sci] 2022 Jul; Vol. 43 (7), pp. 4387-4392. Date of Electronic Publication: 2022 Mar 23. - Publication Year :
- 2022
-
Abstract
- Background: Multiple sclerosis (MS) is the most common cause of nontraumatic chronic neurological disability affecting young adults during their crucial employment years.<br />Objectives: To evaluate patients and disease related factors associated to unemployment in a cohort of relapsing-remitting (RR) MS patients.<br />Methods: We included RRMS patients with a follow-up of at least 1 year. We collected data about years of school education and employment status. Patients underwent a neuropsychological evaluation using the Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS). Demographic and clinical predictors of unemployment were assessed through a multivariable stepwise logistic regression model.<br />Results: We evaluated 260 consecutive RRMS patients. Employed patients were less frequently female (68.4% vs 83.3%, p = 0.006), less disabled (median Expanded Disability Status Scale (EDSS) score: 2.0 (0-7.0) vs 2.5 (0-7.5), p < 0.001), with more years of school education (mean ± standard deviation (SD), years: 13.74 ± 0.30 vs 10.86 ± 3.47, p < 0.001). Female sex and a higher EDSS score resulted associated with a greater risk of unemployment (OR 3.510, 95% CI 1.654-7.448, p = 0.001; OR 1.366, 95% CI 1.074-1.737, p = 0.011, respectively), whereas a greater number of years of schooling and current disease-modifying therapy exposure resulted protective factors (OR 0.788, 95% CI 0.723-0.858, p < 0,001; OR 0.414, 95% CI 0.217-0.790, p = 0.008, respectively).<br />Conclusions: Understanding work is pervasively influenced by consequences of MS, we confirmed the impact of demographic, physical, and cognitive factors on employment status in RRMS patients.<br /> (© 2022. The Author(s).)
Details
- Language :
- English
- ISSN :
- 1590-3478
- Volume :
- 43
- Issue :
- 7
- Database :
- MEDLINE
- Journal :
- Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
- Publication Type :
- Academic Journal
- Accession number :
- 35322339
- Full Text :
- https://doi.org/10.1007/s10072-022-06029-4