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Patient Factors and Temporal Trends Associated with COVID-19 In-hospital Mortality in England: an Observational Study Using Administrative Data

Overview
Publisher Elsevier
Specialty Pulmonary Medicine
Date 2021 Feb 18
PMID 33600777
Citations 77
Authors
Affiliations
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Abstract

Background: 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.

Methods: 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).

Findings: 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.

Interpretation: 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.

Funding: None.

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References
1.
Zakeri R, Bendayan R, Ashworth M, Bean D, Dodhia H, Durbaba S . A case-control and cohort study to determine the relationship between ethnic background and severe COVID-19. EClinicalMedicine. 2020; 28:100574. PMC: 7545271. DOI: 10.1016/j.eclinm.2020.100574. View

2.
Grasselli G, Greco M, Zanella A, Albano G, Antonelli M, Bellani G . Risk Factors Associated With Mortality Among Patients With COVID-19 in Intensive Care Units in Lombardy, Italy. JAMA Intern Med. 2020; 180(10):1345-1355. PMC: 7364371. DOI: 10.1001/jamainternmed.2020.3539. View

3.
Guan W, Ni Z, Hu Y, Liang W, Ou C, He J . Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med. 2020; 382(18):1708-1720. PMC: 7092819. DOI: 10.1056/NEJMoa2002032. View

4.
Deng G, Yin M, Chen X, Zeng F . Clinical determinants for fatality of 44,672 patients with COVID-19. Crit Care. 2020; 24(1):179. PMC: 7187660. DOI: 10.1186/s13054-020-02902-w. View

5.
Korber B, Fischer W, Gnanakaran S, Yoon H, Theiler J, Abfalterer W . Tracking Changes in SARS-CoV-2 Spike: Evidence that D614G Increases Infectivity of the COVID-19 Virus. Cell. 2020; 182(4):812-827.e19. PMC: 7332439. DOI: 10.1016/j.cell.2020.06.043. View