Clinical COVID19 data collection from the uk multiple sclerosis register

Background: The UK MS Register captures longitudinal data directly from people with MS (pwMS) as patient reported outcome measures but also from NHS Trusts via electronic Case Return Form (eCRF) As part of our response to the COVID19 pandemic we designed an anonymised clinical capture instrument to allow clinicians from non affiliated NHS hospitals capture important clinical data on incident cases Here we outline our current clinicians reported findings from these collected data Objectives: Report on patients with Multiple Sclerosis and COVID as reported by UK National Health Service MS clinicians to the UK MS Register Methods: Data were captured using the RedCap platform to design forms and were stored on secured databases at Swansea University Medical School The URL for data capture was shared on social media and via clinician groups to encourage as many clinicians as possible to report hospitalised pwMS and confirmed COVID Variables included: Age, Gender, MS Type, Expanded Disability Status Score (EDSS), Disease Modifying Therapy (DMT) Details, COVID clinical treatment and outcomes Results: Between 27/03/2020 and 14/07/2020, 93 patients with COVID were reported Their mean Age was 53 38 (±14 2) and median EDSS 6 0 Of these 11 patients died with mean Age 63 7(±10 9) Median EDSS 8 0 Multivariate regression showed increased EDSS score to be the most significant factor for mortality (P <0 01) with the other variables (age, gender, disease type, DMT,) not influencing mortality All the patients that died had progressive MS and only one was on a DMT Conclusions: Here we present the UK PwMS, with laboratory confirmed COVID19 as reported by hospital clinicians We found increased disability rather than age or MS type to be the only predictor of mortality These results are strikingly different from the patients reported UK MS register COVID study (separate abstract) that had a much milder COVID illness that led to hospitalisation in only 3% of the cases