External validation of the 4C mortality score among COVID-19 patients admitted to hospital in Ontario, Canada: a retrospective study

Sci Rep. 2021 Sep 20;11(1):18638. doi: 10.1038/s41598-021-97332-1.

Abstract

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, and to examine its performance over time. We conducted an external validation study within a registry of COVID-19 positive hospital admissions in the Kitchener-Waterloo and Hamilton regions of southern Ontario between March 4, 2020 and June 13, 2021. 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. The study included 959 individuals, of whom 224 (23.4%) died in-hospital. Median age was 72 years and 524 individuals (55%) were male. The AUC of the 4C score was 0.77, 95% confidence interval 0.79-0.87. Overall mortality rates across the pre-defined risk groups were 0% (Low), 8.0% (Intermediate), 27.2% (High), and 54.2% (Very High). Wave 1, 2 and 3 values of the AUC were 0.81 (0.76, 0.86), 0.74 (0.69, 0.80), and 0.76 (0.69, 0.83) respectively. The 4C score is a valid tool to prognosticate mortality from COVID-19 in Canadian hospitals and can be used to prioritize care and resources for patients at greatest risk of death.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Aged
  • Aged, 80 and over
  • Area Under Curve
  • COVID-19 / diagnosis
  • COVID-19 / mortality*
  • Female
  • Hospitalization*
  • Humans
  • Male
  • Middle Aged
  • Ontario / epidemiology
  • Reproducibility of Results
  • Retrospective Studies