External validation of the 4C mortality score among COVID-19 patients admitted to hospital in Ontario, Canada: a retrospective study
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 perf...
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2021
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oai:doaj.org-article:30497207b4ac453e84fa1227cc75c8412021-12-02T18:14:39ZExternal validation of the 4C mortality score among COVID-19 patients admitted to hospital in Ontario, Canada: a retrospective study10.1038/s41598-021-97332-12045-2322https://doaj.org/article/30497207b4ac453e84fa1227cc75c8412021-09-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-97332-1https://doaj.org/toc/2045-2322Abstract 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.Aaron JonesTyler PitreMats JunekJessica KapralikRina PatelEdward FengLaura DawsonJennifer L. Y. TsangMyLinh DuongTerence HoMarla K. BeauchampAndrew P. CostaRebecca Kruisselbrinkthe COREG InvestigatorsNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-7 (2021) |
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Medicine R Science Q Aaron Jones Tyler Pitre Mats Junek Jessica Kapralik Rina Patel Edward Feng Laura Dawson Jennifer L. Y. Tsang MyLinh Duong Terence Ho Marla K. Beauchamp Andrew P. Costa Rebecca Kruisselbrink the COREG Investigators External validation of the 4C mortality score among COVID-19 patients admitted to hospital in Ontario, Canada: a retrospective study |
description |
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. |
format |
article |
author |
Aaron Jones Tyler Pitre Mats Junek Jessica Kapralik Rina Patel Edward Feng Laura Dawson Jennifer L. Y. Tsang MyLinh Duong Terence Ho Marla K. Beauchamp Andrew P. Costa Rebecca Kruisselbrink the COREG Investigators |
author_facet |
Aaron Jones Tyler Pitre Mats Junek Jessica Kapralik Rina Patel Edward Feng Laura Dawson Jennifer L. Y. Tsang MyLinh Duong Terence Ho Marla K. Beauchamp Andrew P. Costa Rebecca Kruisselbrink the COREG Investigators |
author_sort |
Aaron Jones |
title |
External validation of the 4C mortality score among COVID-19 patients admitted to hospital in Ontario, Canada: a retrospective study |
title_short |
External validation of the 4C mortality score among COVID-19 patients admitted to hospital in Ontario, Canada: a retrospective study |
title_full |
External validation of the 4C mortality score among COVID-19 patients admitted to hospital in Ontario, Canada: a retrospective study |
title_fullStr |
External validation of the 4C mortality score among COVID-19 patients admitted to hospital in Ontario, Canada: a retrospective study |
title_full_unstemmed |
External validation of the 4C mortality score among COVID-19 patients admitted to hospital in Ontario, Canada: a retrospective study |
title_sort |
external validation of the 4c mortality score among covid-19 patients admitted to hospital in ontario, canada: a retrospective study |
publisher |
Nature Portfolio |
publishDate |
2021 |
url |
https://doaj.org/article/30497207b4ac453e84fa1227cc75c841 |
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