Development and validation of COEWS (COVID-19 Early Warning Score) for hospitalized COVID-19 with laboratory features: A multicontinental retrospective study

Author:

Klén Riku1ORCID,Huespe Ivan A2ORCID,Gregalio Felipe Aníbal2ORCID,Lalueza Blanco Antonio Lalueza3,Pedrera Jimenez Miguel3,Garcia Barrio Noelia3,Valdez Pascual Ruben4,Mirofsky Matias A5,Boietti Bruno2,Gómez-Huelgas Ricardo6,Casas-Rojo José Manuel7,Antón-Santos Juan Miguel7ORCID,Pollan Javier Alberto2,Gómez-Varela David8ORCID

Affiliation:

1. Turku PET Centre, University of Turku and Turku University Hospital

2. Italian Hospital of Buenos Aires

3. 12 de Octubre University Hospital, Research Institute of Hospital 12 de Octubre (imas+12), Complutense University

4. Vélez Sarsfield Hospital

5. Hospital Municipal de Agudos Dr Leónidas Lucero

6. Regional University Hospital of Málaga, Biomedical Research Institute of Málaga (IBIMA), University of Malaga

7. Infanta Cristina University Hospital

8. Division of Pharmacology & Toxicology, Department of Pharmaceutical Sciences, University of Vienna

Abstract

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.

Funder

University of Vienna

Publisher

eLife Sciences Publications, Ltd

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

Reference27 articles.

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