Report 50: Hospitalisation risk for Omicron cases in England
Report 50: Hospitalisation risk for Omicron cases in England
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报告 50：英格兰 Omicron 病例的住院风险
DOI：
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
E. Volz
中科院分区：
文献类型：
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作者：
N. Ferguson;A. Ghani;W. Hinsley;E. Volz
使用S-基因（SGTF）和病例数据的组合，通过（NHS）编号将数据链接到国家管理系统（NIMS）数据库、NHS护理（ECDS）和（SUS）医院事件数据集。住院率的定义是病例在最后一次PCR检测呈阳性后14天内（直至并包括就诊日）在医院的任何就诊记录。次要分析检查了住院时间为一天或多天的就诊子集。我们使用分层条件泊松回归来预测住院状态，人口统计学分层由年龄、性别、种族、地区、标本日期、多重剥夺指数和在某些分析中的疫苗接种状态定义。预测变量为变异和疫苗接种状态。
using a combination of S-gene (SGTF) and Case data were linked by (NHS) number to the National Management System (NIMS) database, the NHS Care (ECDS) and (SUS) hospital episode datasets. Hospital attendance was defined as any record of attendance at a hospital by a case in the 14 days following their last positive PCR test, up to and including the day of attendance. A secondary analysis examined the subset of attendances with a length of stay of one or more days. We used stratified conditional Poisson regression to predict hospitalisation status, with demographic strata defined by age, sex, ethnicity, region, specimen date, index of multiple deprivation and in some analyses, vaccination status. Predictor variables were variant and vaccination status.