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The CCEDRRN COVID-19 Mortality Score to predict death among nonpalliative patients with COVID-19 presenting to
Corinne M Hohl1, Rhonda J Rosychuk2, Patrick M Archambault2
1Department of Emergency Medicine (Hohl, O'Sullivan, Ho), University of British Columbia; Centre for Clinical Epidemiology and Evaluation (Hohl, O'Sullivan, Ho), Vancouver Coastal Health Research Institute, Vancouver, BC; Department of Pediatrics (Rosychuk), University of Alberta, Edmonton, Alta.; Department of Family Medicine and Emergency Medicine (Archambault), Université Laval, Québec, Que.; Centre de recherche du Centre intégré de santé et de services sociaux de Chaudière-Appalaches (Archambault), Lévis, Que.; Department of Emergency Medicine (Leeies, Jelic) and Section of Critical Care Medicine (Leeies), Faculty of Health Sciences, University of Manitoba, Winnipeg, Man.; Centre de recherche (Mercier), CHU de Québec, Université Laval; VITAM (Centre de recherche en santé durable) (Mercier), Québec, Que.; Department of Emergency Medicine (Clark), McGill University, Montréal, Que.; Department of Emergency Medicine and Community Health Sciences (Innes), University of Calgary, Calgary, Alta.; Department of Emergency Medicine (Brooks, Sivilotti), Queen's University, Kingston, Ont.; Department of Emergency Medicine (Hayward), University of Alberta, Edmonton, Alta.; Division of Emergency Medicine (Welsford), McMaster University; Hamilton Health Sciences (Welsford), Hamilton, Ont.; Kingston Health Sciences Centre (Sivilotti), Kingston, Ont.; Emergency Services (Morrison), Sunnybrook Health Sciences Centre; Division of Emergency Medicine (Morrison), Department of Medicine, University of Toronto, Toronto, Ont.; Department of Emergency Medicine (Perry), University of Ottawa; Ottawa Hospital Research Institute (Perry), Ottawa, Ont. corinne.hohl@ubc.ca.
Insights
A new COVID-19 mortality score accurately predicts patient death using emergency department data. This tool aids in critical care resource allocation and goals-of-care discussions.
Area of Science:
- Emergency Medicine
- Infectious Diseases
- Clinical Prediction Models
Background:
- Predicting COVID-19 mortality at emergency department presentation is crucial for resource allocation and care decisions.
- The study focused on nonpalliative adult patients with confirmed COVID-19.
Purpose of the Study:
- To develop and validate a clinical score for predicting mortality in emergency department and in-hospital settings for COVID-19 patients.
- To aid in ethical allocation of critical care resources.
Main Methods:
- Observational cohort study involving 46 hospitals across Canada (Canadian COVID-19 Emergency Department Rapid Response Network - CCEDRRN).
- Logistic regression used to develop the CCEDRRN COVID-19 Mortality Score in a derivation cohort and validated in a separate cohort.
- Included variables: age, sex, residence type, arrival mode, chest pain, severe liver disease, respiratory rate, and respiratory support level.
Main Results:
- The CCEDRRN COVID-19 Mortality Score demonstrated high predictive accuracy (AUC 0.92 in derivation and validation).
- A score of 6 or less indicated low risk for in-hospital death (0.1% mortality, 99.9% NPV).
- Patients with scores of 15 or higher had an observed mortality rate of 81.0%.
Conclusions:
- The CCEDRRN COVID-19 Mortality Score is a validated, simple tool for predicting COVID-19 mortality using readily available emergency department data.
- The score facilitates level-of-care discussions and resource management, particularly during high-demand periods.
- The score was primarily developed and validated in unvaccinated patients before widespread variant circulation and updated treatments.
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 score had excellent calibration. These results suggest that scores of 6 or less would categorize patients as being at low risk for in-hospital death, with a negative predictive value of 99.9%. Patients in the low-risk group had an in-hospital mortality rate of 0.1%. Patients with a score of 15 or higher had an observed mortality rate of 81.0%.
Interpretation:
The CCEDRRN COVID-19 Mortality Score is a simple score that can be used for level-of-care discussions with patients and in situations of critical care resource constraints to accurately predict death using variables available on emergency department arrival. The score was derived and validated mostly in unvaccinated patients, and before variants of concern were circulating widely and newer treatment regimens implemented in Canada.
Study Registration:
ClinicalTrials.gov, no. NCT04702945.
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