Objectives: To analyze the symptoms and severity of coronavirus disease 2019 (COVID-19) in people with multiple sclerosis (pwMS) on disease-modifying therapies using data from the COVID-19 in multiple sclerosis (MS) Global Data Sharing Initiative dataset.
Methods: The open-access COVID-19 in MS Global Data Sharing Initiative dataset was obtained through credentialed access using PhysioNet. The variables analyzed included BMI, symptoms of COVID-19, age, current use of disease-modifying therapy (DMT), efficacy of DMT, comorbidities, hospitalization status, and type of MS. A linear regression analysis was completed. Data analysis and visualization were completed using STATA , R-Studio , Python and its associated libraries, including NumPy, Pandas, and Matplotlib.
Results: A total of 1141 participants were included in the analysis. 904 women and 237 men were diagnosed with MS. Among the pwMS included in the study; 208 (19.54%) had a suspected infection with COVID-19 and only 49 (5.25%) were confirmed. Any COVID-19 symptom was present in 360 individuals. The commonly reported DMT agents included dimethyl fumarate (12.71%) and fingolimod (10.17%). 101 in total (8.85%) reported not using any DMT. Factors associated with hospitalization and/or admission to the ICU included having any comorbidity (0.01), neuromuscular disorder (0.046), hypertension (0.005), chronic kidney disease (0.001), and immunodeficiency (0.003). The type of MS, the duration of the disease, and high-efficacy DMT therapy did not have a statistically significant influence on hospitalization.
Conclusion: This study underscores the importance of comorbidities, especially neuromuscular disorders, hypertension, chronic kidney disease, and immunodeficiencies, as possible prognostic indicators for worse outcomes of COVID-19 in pwMS. On the contrary, the type of MS, the duration of the disease, and the efficacy of disease-modifying therapy did not significantly affect the severity of the symptoms of COVID-19 in this cohort.
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| http://dx.doi.org/10.1097/MS9.0000000000001676 | DOI Listing |
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