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Development and validation of COEWS (COVID-19 Early Warning Score) for hospitalized COVID-19 with laboratory features: A multicontinental retrospective study
BACKGROUND: The emergence of new SARS-CoV-2 variants with significant immune-evasiveness, the relaxation of measures for reducing the number of infections, the waning of immune protection (particularly in high-risk population groups), and the low uptake of new vaccine boosters, forecast new waves of...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10479961/ https://www.ncbi.nlm.nih.gov/pubmed/37615346 http://dx.doi.org/10.7554/eLife.85618 |
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author | Klén, Riku Huespe, Ivan A Gregalio, Felipe Aníbal Lalueza Blanco, Antonio Lalueza Pedrera Jimenez, Miguel Garcia Barrio, Noelia Valdez, Pascual Ruben Mirofsky, Matias A Boietti, Bruno Gómez-Huelgas, Ricardo Casas-Rojo, José Manuel Antón-Santos, Juan Miguel Pollan, Javier Alberto Gómez-Varela, David |
author_facet | Klén, Riku Huespe, Ivan A Gregalio, Felipe Aníbal Lalueza Blanco, Antonio Lalueza Pedrera Jimenez, Miguel Garcia Barrio, Noelia Valdez, Pascual Ruben Mirofsky, Matias A Boietti, Bruno Gómez-Huelgas, Ricardo Casas-Rojo, José Manuel Antón-Santos, Juan Miguel Pollan, Javier Alberto Gómez-Varela, David |
author_sort | Klén, Riku |
collection | PubMed |
description | BACKGROUND: The emergence of new SARS-CoV-2 variants with significant immune-evasiveness, the relaxation of measures for reducing the number of infections, the waning of immune protection (particularly in high-risk population groups), and the low uptake of new vaccine boosters, forecast new waves of hospitalizations and admission to intensive care units. There is an urgent need for easily implementable and clinically effective Early Warning Scores (EWSs) that can predict the risk of complications within the next 24–48 hr. Although EWSs have been used in the evaluation of COVID-19 patients, there are several clinical limitations to their use. Moreover, no models have been tested on geographically distinct populations or population groups with varying levels of immune protection. METHODS: We developed and validated COVID-19 Early Warning Score (COEWS), an EWS that is automatically calculated solely from laboratory parameters that are widely available and affordable. We benchmarked COEWS against the widely used NEWS2. We also evaluated the predictive performance of vaccinated and unvaccinated patients. RESULTS: The variables of the COEWS predictive model were selected based on their predictive coefficients and on the wide availability of these laboratory variables. The final model included complete blood count, blood glucose, and oxygen saturation features. To make COEWS more actionable in real clinical situations, we transformed the predictive coefficients of the COEWS model into individual scores for each selected feature. The global score serves as an easy-to-calculate measure indicating the risk of a patient developing the combined outcome of mechanical ventilation or death within the next 48 hr. The discrimination in the external validation cohort was 0.743 (95% confidence interval [CI]: 0.703–0.784) for the COEWS score performed with coefficients and 0.700 (95% CI: 0.654–0.745) for the COEWS performed with scores. The area under the receiver operating characteristic curve (AUROC) was similar in vaccinated and unvaccinated patients. Additionally, we observed that the AUROC of the NEWS2 was 0.677 (95% CI: 0.601–0.752) in vaccinated patients and 0.648 (95% CI: 0.608–0.689) in unvaccinated patients. CONCLUSIONS: The COEWS score predicts death or MV within the next 48 hr based on routine and widely available laboratory measurements. The extensive external validation, its high performance, its ease of use, and its positive benchmark in comparison with the widely used NEWS2 position COEWS as a new reference tool for assisting clinical decisions and improving patient care in the upcoming pandemic waves. FUNDING: University of Vienna. |
format | Online Article Text |
id | pubmed-10479961 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-104799612023-09-06 Development and validation of COEWS (COVID-19 Early Warning Score) for hospitalized COVID-19 with laboratory features: A multicontinental retrospective study Klén, Riku Huespe, Ivan A Gregalio, Felipe Aníbal Lalueza Blanco, Antonio Lalueza Pedrera Jimenez, Miguel Garcia Barrio, Noelia Valdez, Pascual Ruben Mirofsky, Matias A Boietti, Bruno Gómez-Huelgas, Ricardo Casas-Rojo, José Manuel Antón-Santos, Juan Miguel Pollan, Javier Alberto Gómez-Varela, David eLife Epidemiology and Global Health BACKGROUND: The emergence of new SARS-CoV-2 variants with significant immune-evasiveness, the relaxation of measures for reducing the number of infections, the waning of immune protection (particularly in high-risk population groups), and the low uptake of new vaccine boosters, forecast new waves of hospitalizations and admission to intensive care units. There is an urgent need for easily implementable and clinically effective Early Warning Scores (EWSs) that can predict the risk of complications within the next 24–48 hr. Although EWSs have been used in the evaluation of COVID-19 patients, there are several clinical limitations to their use. Moreover, no models have been tested on geographically distinct populations or population groups with varying levels of immune protection. METHODS: We developed and validated COVID-19 Early Warning Score (COEWS), an EWS that is automatically calculated solely from laboratory parameters that are widely available and affordable. We benchmarked COEWS against the widely used NEWS2. We also evaluated the predictive performance of vaccinated and unvaccinated patients. RESULTS: The variables of the COEWS predictive model were selected based on their predictive coefficients and on the wide availability of these laboratory variables. The final model included complete blood count, blood glucose, and oxygen saturation features. To make COEWS more actionable in real clinical situations, we transformed the predictive coefficients of the COEWS model into individual scores for each selected feature. The global score serves as an easy-to-calculate measure indicating the risk of a patient developing the combined outcome of mechanical ventilation or death within the next 48 hr. The discrimination in the external validation cohort was 0.743 (95% confidence interval [CI]: 0.703–0.784) for the COEWS score performed with coefficients and 0.700 (95% CI: 0.654–0.745) for the COEWS performed with scores. The area under the receiver operating characteristic curve (AUROC) was similar in vaccinated and unvaccinated patients. Additionally, we observed that the AUROC of the NEWS2 was 0.677 (95% CI: 0.601–0.752) in vaccinated patients and 0.648 (95% CI: 0.608–0.689) in unvaccinated patients. CONCLUSIONS: The COEWS score predicts death or MV within the next 48 hr based on routine and widely available laboratory measurements. The extensive external validation, its high performance, its ease of use, and its positive benchmark in comparison with the widely used NEWS2 position COEWS as a new reference tool for assisting clinical decisions and improving patient care in the upcoming pandemic waves. FUNDING: University of Vienna. eLife Sciences Publications, Ltd 2023-08-24 /pmc/articles/PMC10479961/ /pubmed/37615346 http://dx.doi.org/10.7554/eLife.85618 Text en © 2023, Klén, Huespe et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Epidemiology and Global Health Klén, Riku Huespe, Ivan A Gregalio, Felipe Aníbal Lalueza Blanco, Antonio Lalueza Pedrera Jimenez, Miguel Garcia Barrio, Noelia Valdez, Pascual Ruben Mirofsky, Matias A Boietti, Bruno Gómez-Huelgas, Ricardo Casas-Rojo, José Manuel Antón-Santos, Juan Miguel Pollan, Javier Alberto Gómez-Varela, David Development and validation of COEWS (COVID-19 Early Warning Score) for hospitalized COVID-19 with laboratory features: A multicontinental retrospective study |
title | Development and validation of COEWS (COVID-19 Early Warning Score) for hospitalized COVID-19 with laboratory features: A multicontinental retrospective study |
title_full | Development and validation of COEWS (COVID-19 Early Warning Score) for hospitalized COVID-19 with laboratory features: A multicontinental retrospective study |
title_fullStr | Development and validation of COEWS (COVID-19 Early Warning Score) for hospitalized COVID-19 with laboratory features: A multicontinental retrospective study |
title_full_unstemmed | Development and validation of COEWS (COVID-19 Early Warning Score) for hospitalized COVID-19 with laboratory features: A multicontinental retrospective study |
title_short | Development and validation of COEWS (COVID-19 Early Warning Score) for hospitalized COVID-19 with laboratory features: A multicontinental retrospective study |
title_sort | development and validation of coews (covid-19 early warning score) for hospitalized covid-19 with laboratory features: a multicontinental retrospective study |
topic | Epidemiology and Global Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10479961/ https://www.ncbi.nlm.nih.gov/pubmed/37615346 http://dx.doi.org/10.7554/eLife.85618 |
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