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COVID-19 in people with multiple sclerosis: A global data sharing initiative.
- Source :
-
Multiple sclerosis (Houndmills, Basingstoke, England) [Mult Scler] 2020 Sep; Vol. 26 (10), pp. 1157-1162. Date of Electronic Publication: 2020 Jul 14. - Publication Year :
- 2020
-
Abstract
- Background: We need high-quality data to assess the determinants for COVID-19 severity in people with MS (PwMS). Several studies have recently emerged but there is great benefit in aligning data collection efforts at a global scale.<br />Objectives: Our mission is to scale-up COVID-19 data collection efforts and provide the MS community with data-driven insights as soon as possible.<br />Methods: Numerous stakeholders were brought together. Small dedicated interdisciplinary task forces were created to speed-up the formulation of the study design and work plan. First step was to agree upon a COVID-19 MS core data set. Second, we worked on providing a user-friendly and rapid pipeline to share COVID-19 data at a global scale.<br />Results: The COVID-19 MS core data set was agreed within 48 hours. To date, 23 data collection partners are involved and the first data imports have been performed successfully. Data processing and analysis is an on-going process.<br />Conclusions: We reached a consensus on a core data set and established data sharing processes with multiple partners to address an urgent need for information to guide clinical practice. First results show that partners are motivated to share data to attain the ultimate joint goal: better understand the effect of COVID-19 in PwMS.
- Subjects :
- Betacoronavirus
COVID-19
Coronavirus Infections complications
Coronavirus Infections therapy
Data Collection
Humans
Information Dissemination
International Cooperation
Multiple Sclerosis complications
Pandemics
Pneumonia, Viral complications
Pneumonia, Viral therapy
Risk Factors
SARS-CoV-2
Treatment Outcome
Coronavirus Infections physiopathology
Multiple Sclerosis therapy
Pneumonia, Viral physiopathology
Registries
Subjects
Details
- Language :
- English
- ISSN :
- 1477-0970
- Volume :
- 26
- Issue :
- 10
- Database :
- MEDLINE
- Journal :
- Multiple sclerosis (Houndmills, Basingstoke, England)
- Publication Type :
- Academic Journal
- Accession number :
- 32662757
- Full Text :
- https://doi.org/10.1177/1352458520941485