Patient factors and temporal trends associated with COVID-19 in-hospital mortality in England: an observational study using administrative data.
Patient factors and temporal trends associated with COVID-19 in-hospital mortality in England: an observational study using administrative data.
复制标题
DOI：
10.1016/s2213-2600(20)30579-8
复制
发表时间：
2021-04
期刊：
影响因子：
--
通讯作者：
Briggs TWR
中科院分区：
文献类型：
--
作者：
Navaratnam AV;Gray WK;Day J;Wendon J;Briggs TWR
关于COVID-19对英格兰全部医院人口的影响的分析一直缺乏。我们的目标是在大流行的早期阶段提供英格兰所有COVID-19住院患者的全面描述，并确定随着大流行的发展影响死亡率的因素。这是一项使用医院事件统计管理数据集的回顾性探索性分析。所有在2020年3月1日至5月31日期间在英格兰完成住院（活着或死亡出院）并在入院时或住院期间被诊断为COVID-19的18岁或以上患者都被纳入其中。院内死亡是主要关注的结局。采用多水平logistic回归对死亡与以下几个协变量之间的关系进行建模：年龄、性别、剥夺（多重剥夺指数）、种族、虚弱（医院虚弱风险评分）、合并症的存在（Charlson合并症指数项目）和出院日期（无论是活着还是死亡）。研究期间出院成人COVID-19患者91 541例，其中住院死亡28 200例（30.8%）。最终的多层逻辑回归模型将年龄、剥夺评分和出院日期作为连续变量，将性别、种族和Charlson共病指数项目作为分类变量。在该模型中，院内死亡的重要预测因子包括年龄较大（使用受限三次样条建模）、男性（1.457[1.408 - 1.509]）、更严重的剥夺（1.002[1.001 - 1.003]）、亚洲人（1.211[1.128 - 1.299]）或混合种族（1.317 [1.080 - 1.605]vs白人），以及大多数评估的合并症，包括中度或重度肝病（5.433[4.618 - 6.392]）。较晚的出院日期与较低的死亡几率相关（0.977 [0.976 - 0.978]）；调整后的住院死亡率大体上呈线性显著提高，从3月第一周的52.2%提高到5月最后一周的16.8%。随着时间的推移，COVID-19患者住院死亡率调整后概率的降低可能反映了医院策略和临床流程变化的影响。应彻底调查所观察到的死亡率下降的原因，以便为今后疫情的应对提供信息。与我们基于医院的分析相比，基于社区的研究报告中某些少数民族群体的死亡率更高，这可能部分反映了高危人群的感染率差异、感染后病情加重的倾向以及寻求健康的行为。没有。
Analysis of the effect of COVID-19 on the complete hospital population in England has been lacking. Our aim was to provide a comprehensive account of all hospitalised patients with COVID-19 in England during the early phase of the pandemic and to identify the factors that influenced mortality as the pandemic evolved. This was a retrospective exploratory analysis using the Hospital Episode Statistics administrative dataset. All patients aged 18 years or older in England who completed a hospital stay (were discharged alive or died) between March 1 and May 31, 2020, and had a diagnosis of COVID-19 on admission or during their stay were included. In-hospital death was the primary outcome of interest. Multilevel logistic regression was used to model the relationship between death and several covariates: age, sex, deprivation (Index of Multiple Deprivation), ethnicity, frailty (Hospital Frailty Risk Score), presence of comorbidities (Charlson Comorbidity Index items), and date of discharge (whether alive or deceased). 91 541 adult patients with COVID-19 were discharged during the study period, among which 28 200 (30·8%) in-hospital deaths occurred. The final multilevel logistic regression model accounted for age, deprivation score, and date of discharge as continuous variables, and sex, ethnicity, and Charlson Comorbidity Index items as categorical variables. In this model, significant predictors of in-hospital death included older age (modelled using restricted cubic splines), male sex (1·457 [1·408–1·509]), greater deprivation (1·002 [1·001–1·003]), Asian (1·211 [1·128–1·299]) or mixed ethnicity (1·317 [1·080–1·605]; vs White ethnicity), and most of the assessed comorbidities, including moderate or severe liver disease (5·433 [4·618–6·392]). Later date of discharge was associated with a lower odds of death (0·977 [0·976–0·978]); adjusted in-hospital mortality improved significantly in a broadly linear fashion, from 52·2% in the first week of March to 16·8% in the last week of May. Reductions in the adjusted probability of in-hospital mortality for COVID-19 patients over time might reflect the impact of changes in hospital strategy and clinical processes. The reasons for the observed improvements in mortality should be thoroughly investigated to inform the response to future outbreaks. The higher mortality rate reported for certain ethnic minority groups in community-based studies compared with our hospital-based analysis might partly reflect differential infection rates in those at greatest risk, propensity to become severely ill once infected, and health-seeking behaviours. None.