Patient-level dataset to study the effect of COVID-19 in people with Multiple Sclerosis

Multiple Sclerosis (MS) is an inflammatory autoimmune disease of the central nervous system, causing increased vulnerability to infections and disability among young adults. Ever since the coronavirus disease 2019 (COVID-19) outbreak, caused by severe acute respiratory syndrome coronavirus 2 infections, there have been concerns among people with MS (PwMS) about the potential interactions between various disease-modifying therapies and COVID-19. The COVID-19 in MS Global Data Sharing Initiative (GDSI) was initiated in 2020 to address these concerns. This paper focuses on the anonymisation and open-sourcing of a GDSI sub-dataset, comprising data entered by people with MS and clinicians using a fast data entry tool. The dataset includes demographics, comorbidities, hospital stay, and COVID-19 symptoms of PwMS. The dataset can be used to perform different statistical analyses to improve our understanding of COVID-19 in MS. Furthermore, this dataset can also be used within the context of educational activities to educate different stakeholders on the complex data science topics that were used within the GDSI.

多发性硬化症（MS）是一种中枢神经系统炎症性自身免疫性疾病，导致年轻成人易感染并出现残疾。自2019年冠状病毒病（COVID-19）爆发以来，由严重急性呼吸综合征冠状病毒2感染引起，多发性硬化症患者（PwMS）对各种疾病修饰疗法与COVID-19之间潜在相互作用表示担忧。2020年启动了COVID-19在MS全球数据共享倡议（GDSI），旨在解决这些担忧。本文聚焦于对GDSI子数据集的匿名化和开源，该子数据集包括多发性硬化症患者及临床医生使用快速数据录入工具输入的数据。该数据集包括人口统计学数据、合并症、住院情况和PwMS的COVID-19症状。该数据集可用于执行不同的统计分析，以增进我们对MS中COVID-19的理解。此外，该数据集还可以在教育活动中使用，以教育不同利益相关者关于GDSI中使用的复杂数据科学主题。