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researchsquare; 2021.
Preprint in English | PREPRINT-RESEARCHSQUARE | ID: ppzbmed-10.21203.rs.3.rs-268410.v1

ABSTRACT

Objectives: Risk prediction scores are important tools to support clinical decision-making for patients with coronavirus disease (COVID-19). The objective of this paper was to validate the 4C mortality score, originally developed in the United Kingdom, for a Canadian population. Methods: We conducted an external validation study within a registry of COVID-19 positive emergency department visits and hospital admissions in the Kitchener-Waterloo and Hamilton regions of southern Ontario between March 4 and January 9, 2020.  We examined the validity of the 4C score to prognosticate in-hospital mortality using the area under the receiver operating characteristic curve (AUC) with 95% confidence intervals calculated via bootstrapping. Results: The study included 560 individuals, of whom 115 (20.5%) died in-hospital. Median age was 69 years and 281 individuals (51%) were male. The AUC of the 4C score was 0.83, 95% confidence interval 0.79-0.87. Mortality rates across the pre-defined risk groups were 0% (Low), 3.2% (Intermediate), 25.9% (High), and 59.5% (Very High). The AUC was 0.80 (0.76-0.85) among hospital inpatients.  Interpretation: The 4C score is a valid tool to prognosticate mortality from COVID-19 in Canadian emergency departments and hospitals. 


Subject(s)
COVID-19 , Coronavirus Infections
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