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Updated: Oct 16, 2025

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
COVID-19 in Multiple Sclerosis: Clinically reported outcomes from the UK Multiple Sclerosis Register
R M Middleton1, E M Craig1, W J Rodgers1
1Population Data Science, School of Medicine, Singleton Park, Swansea University, SA2 8PP, United Kingdom.
Background:
In March 2020, the United Kingdom Multiple Sclerosis Register (UKMSR) established an electronic case return form, designed collaboratively by MS neurologists, to record data about COVID-19 infections in people with MS (pwMS).
Objectives:
Examine how hospital admission and mortality are affected by disability, age and disease modifying treatments (DMTs) in people with Multiple Sclerosis with COVID-19.
Methods:
Anonymised data were submitted by clinical teams. Regression models were tested for predictors of hospitalisation and mortality outcomes. Separate analyzes compared the first and second 'waves' of the pandemic.
Results:
Univariable analysis found hospitalisation and mortality were associated with increasing age, male gender, comorbidities, severe disability, and progressive MS; severe disability showed the highest magnitude of association. Being on a DMT was associated with a small, lower risk. Multivariable analysis found only age and male gender were significant. Post hoc analysis demonstrated that factors were significant for hospitalisation but not mortality. In the second wave, hospitalisation and mortality were lower. Separate models of the first and second wave using age and gender found they had a more important role in the second wave.
Conclusions:
Features associated with poor outcome in COVID-19 are similar to other populations and being on a DMT was not found to be associated with adverse outcomes, consistent with smaller studies. Once in hospital, no factors were predictive of mortality. Reassuringly, mortality appears lower in the second wave.
Insights
COVID-19 outcomes in people with Multiple Sclerosis (MS) were analyzed. Severe disability and older age increased hospitalization and mortality risk, while disease-modifying treatments (DMTs) showed no adverse association.
Area of Science:
- Neurology
- Infectious Diseases
- Epidemiology
Background:
- The United Kingdom Multiple Sclerosis Register (UKMSR) initiated an electronic data collection system in March 2020 to track COVID-19 in people with Multiple Sclerosis (pwMS).
- This system was developed in collaboration with MS neurologists to ensure accurate data capture.
Purpose of the Study:
- To investigate the impact of disability, age, and disease-modifying treatments (DMTs) on hospital admission and mortality rates in pwMS diagnosed with COVID-19.
- To compare outcomes between the first and second waves of the pandemic.
Main Methods:
- Anonymized data from clinical teams were analyzed using regression models to identify predictors of hospitalization and mortality.
- Separate analyses were conducted to compare outcomes during the first and second waves of the COVID-19 pandemic.
Main Results:
- Univariable analysis indicated that increasing age, male gender, comorbidities, severe disability, and progressive MS were associated with higher risks of hospitalization and mortality, with severe disability showing the strongest link.
- Multivariable analysis identified only age and male gender as significant predictors for adverse outcomes.
- Hospitalization and mortality rates were lower during the second wave compared to the first wave.
Conclusions:
- Risk factors for poor COVID-19 outcomes in people with MS are similar to those in the general population.
- Disease-modifying treatments (DMTs) were not associated with adverse outcomes in pwMS with COVID-19.
- Mortality rates for pwMS with COVID-19 appeared lower during the second wave of the pandemic.
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