作者
Corinne M Hohl, Rhonda J Rosychuk, Patrick M Archambault, Fiona O’Sullivan, Murdoch Leeies, Éric Mercier, Gregory Clark, Grant D Innes, Steven C Brooks, Jake Hayward, Vi Ho, Tomislav Jelic, Michelle Welsford, Marco LA Sivilotti, Laurie J Morrison, Jeffrey J Perry
发表日期
2022/1/1
期刊
Canadian Medical Association Open Access Journal
卷号
10
期号
1
页码范围
E90-E99
出版商
Canadian Medical Association Open Access Journal
简介
Background
Predicting mortality from COVID-19 using information available when patients present to the emergency department can inform goals-of-care decisions and assist with ethical allocation of critical care resources. The study objective was to develop and validate a clinical score to predict emergency department and in-hospital mortality among consecutive nonpalliative patients with COVID-19; in this study, we define palliative patients as those who do not want resuscitative measures, such as intubation, intensive care unit care or cardiopulmonary resuscitation.
Methods
This derivation and validation study used observational cohort data recruited from 46 hospitals in 8 Canadian provinces participating in the Canadian COVID-19 Emergency Department Rapid Response Network (CCEDRRN). We included adult (age ≥ 18 yr) nonpalliative patients with confirmed COVID-19 who presented to the emergency department of a participating site between Mar. 1, 2020, and Jan. 31, 2021. We randomly assigned hospitals to derivation or validation, and prespecified clinical variables as candidate predictors. We used logistic regression to develop the score in a derivation cohort and examined its performance in predicting emergency department and in-hospital mortality in a validation cohort.
Results
Of 8761 eligible patients, 618 (7.0%) died. The CCEDRRN COVID-19 Mortality Score included age, sex, type of residence, arrival mode, chest pain, severe liver disease, respiratory rate and level of respiratory support. The area under the curve was 0.92 (95% confidence interval [CI] 0.90–0.93) in derivation and 0.92 (95% CI 0.90–0.93) in validation. The …
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