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OpenSAFELY: factors associated with COVID-19 death in 17 million patients
Nature ( IF 64.8 ) Pub Date : 2020-07-08 , DOI: 10.1038/s41586-020-2521-4
Elizabeth J Williamson 1 , Alex J Walker 2 , Krishnan Bhaskaran 1 , Seb Bacon 2 , Chris Bates 3 , Caroline E Morton 2 , Helen J Curtis 2 , Amir Mehrkar 2 , David Evans 2 , Peter Inglesby 2 , Jonathan Cockburn 3 , Helen I McDonald 1, 4 , Brian MacKenna 2 , Laurie Tomlinson 1 , Ian J Douglas 1 , Christopher T Rentsch 1 , Rohini Mathur 1 , Angel Y S Wong 1 , Richard Grieve 1 , David Harrison 5 , Harriet Forbes 1 , Anna Schultze 1 , Richard Croker 2 , John Parry 3 , Frank Hester 3 , Sam Harper 3 , Rafael Perera 2 , Stephen J W Evans 1 , Liam Smeeth 1, 4 , Ben Goldacre 2
Affiliation  

Coronavirus disease 2019 (COVID-19) has rapidly affected mortality worldwide1. There is unprecedented urgency to understand who is most at risk of severe outcomes, and this requires new approaches for the timely analysis of large datasets. Working on behalf of NHS England, we created OpenSAFELY—a secure health analytics platform that covers 40% of all patients in England and holds patient data within the existing data centre of a major vendor of primary care electronic health records. Here we used OpenSAFELY to examine factors associated with COVID-19-related death. Primary care records of 17,278,392 adults were pseudonymously linked to 10,926 COVID-19-related deaths. COVID-19-related death was associated with: being male (hazard ratio (HR) 1.59 (95% confidence interval 1.53–1.65)); greater age and deprivation (both with a strong gradient); diabetes; severe asthma; and various other medical conditions. Compared with people of white ethnicity, Black and South Asian people were at higher risk, even after adjustment for other factors (HR 1.48 (1.29–1.69) and 1.45 (1.32–1.58), respectively). We have quantified a range of clinical factors associated with COVID-19-related death in one of the largest cohort studies on this topic so far. More patient records are rapidly being added to OpenSAFELY, we will update and extend our results regularly. OpenSAFELY, a new health analytics platform that includes data from over 17 million adult NHS patients in England, is used to examine factors associated with COVID-19-related death.

中文翻译:

OpenSAFELY:与 1700 万患者 COVID-19 死亡相关的因素

2019 年冠状病毒病 (COVID-19) 迅速影响了全球死亡率1。了解谁最有可能遭受严重后果的问题变得前所未有的紧迫,这需要新的方法来及时分析大型数据集。我们代表英格兰 NHS 创建了 OpenSAFELY,这是一个安全的健康分析平台,覆盖英格兰 40% 的患者,并将患者数据保存在初级保健电子健康记录主要供应商的现有数据中心内。在这里,我们使用 OpenSAFELY 检查与 COVID-19 相关死亡相关的因素。17,278,392 名成年人的初级保健记录与 10,926 例与 COVID-19 相关的死亡有匿名关联。COVID-19 相关死亡与以下因素相关: 男性(风险比 (HR) 1.59(95% 置信区间 1.53–1.65));更大的年龄和剥夺(两者都有很强的梯度);糖尿病; 严重哮喘;以及各种其他医疗状况。与白人相比,黑人和南亚人的风险更高,即使在调整其他因素后也是如此(HR 分别为 1.48 (1.29–1.69) 和 1.45 (1.32–1.58))。在迄今为止有关该主题的最大队列研究之一中,我们量化了与 COVID-19 相关死亡相关的一系列临床因素。更多患者记录正在迅速添加到 OpenSAFELY,我们将定期更新和扩展我们的结果。OpenSAFELY 是一个新的健康分析平台,包含来自英格兰超过 1700 万成年 NHS 患者的数据,用于检查与 COVID-19 相关死亡相关的因素。
更新日期:2020-07-08
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