Author:
Hohl Corinne M.,Rosychuk Rhonda J.,Archambault Patrick M.,O’Sullivan Fiona,Leeies Murdoch,Mercier Éric,Clark Gregory,Innes Grant D.,Brooks Steven C.,Hayward Jake,Ho Vi,Jelic Tomislav,Welsford Michelle,Sivilotti Marco L.A.,Morrison Laurie J.,Perry Jeffrey J.
Abstract
ABSTRACTBackgroundPredicting mortality from coronavirus disease 2019 (COVID-19) using information available when patients present to the Emergency Department (ED) can inform goals-of-care decisions and assist with ethical allocation of critical care resources.MethodsWe conducted an observational study to develop and validate a clinical score to predict ED and in-hospital mortality among consecutive non-palliative COVID-19 patients. We recruited from 44 hospitals participating in the Canadian COVID-19 ED Rapid Response Network (CCEDRRN) between March 1, 2020 and January 31, 2021. We randomly assigned hospitals to derivation or validation, and pre-specified clinical variables as candidate predictors. We used logistic regression to develop the score in a derivation cohort, and examined its performance in predicting ED and in-hospital mortality in a validation cohort.ResultsOf 8,761 eligible patients, 618 (7·01%) died. The 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 intervals [CI] 0·91–0·93) in derivation and 0·92 (95%CI 0·89–0·93) in validation. The score had excellent calibration. Above a score of 15, the observed mortality was 81·0% (81/100) with a specificity of 98·8% (95%CI 99·5–99·9%).InterpretationThe CCEDRRN COVID Mortality Score is a simple score that accurately predicts mortality with variables that are available on patient arrival without the need for diagnostic tests.Trial registrationClinicaltrials.gov, NCT04702945
Publisher
Cold Spring Harbor Laboratory