Development and validation of COEWS (COVID-19 Early Warning Score) for hospitalized COVID-19 with laboratory features: a multicontinental retrospective study
- University of Turku, Finland
- Hospital Italiano de Buenos Aires, Argentina
- Hospital Universitario 12 De Octubre, Spain
- Vélez Sarsfield Hospital, Argentina
- Hospital Municipal de Agudos Dr Leónidas Lucero, Argentina
- University of Malaga, Spain
- Infanta Cristina University Hospital, Spain
- University of Vienna, Austria
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 (ICUs). 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 to 48 hours. 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 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 hours. 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 mechanical ventilation within the next 48 hours 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.
Data availability
The databases used in this article are not freely available because they are the property of the '12 de Octubre University Hospital' from Spain and the 'Sociedad Argentina de Medicina' from Argentina. If any researcher wants to use this data, please send a message to either Dr. Antonio Lalueza (lalueza@hotmail.com) or to Dr. Ivan Alfredo Huespe (ivan.huespe@hospitalitaliano.org.ar) including a project proposal. The data will be only available for non-commercial proposals. The dataset used for Figure 2 can be found in the Supplementary data tables.
Article and author information
Author details
Felipe Aníbal Gregalio
Juan Miguel Antón-Santos
David Gómez-Varela
Funding
University of Vienna
- David Gómez-Varela
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: The SEMI-COVID-19 Registry and the COVID registries of 12 de Octubre and the Costa del Sol hospitals have been approved by the Provincial Research Ethics Committee of Malaga (Spain; C.I.F. number: 0-9150013-B). Institutional review boards approved each participating site in the Argentinian COVID-19 Network study (approval numbers: 1575, 5562, and 5606).
Copyright
© 2023, Klén et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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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
eLife 12:e85618.
https://doi.org/10.7554/eLife.85618
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Methods: Untargeted metabolomics was performed on serum samples of 5,004 children aged 6-59 months, a subset of participants from the Brazilian National Survey on Child Nutrition (ENANI-2019). ECD was assessed using the Survey of Well-being of Young Children's milestones questionnaire. The graded response model was used to estimate developmental age. Developmental quotient (DQ) was calculated as the developmental age divided by chronological age. Partial least square regression selected metabolites with a variable importance projection ≥ 1. The interaction between significant metabolites and the child's age was tested.
Results: Twenty-eight top-ranked metabolites were included in linear regression models adjusted for the child's nutritional status, diet quality, and infant age. Cresol sulfate (β = -0.07; adjusted-p < 0.001), hippuric acid (β = -0.06; adjusted-p < 0.001), phenylacetylglutamine (β = -0.06; adjusted-p < 0.001), and trimethylamine-N-oxide (β = -0.05; adjusted-p = 0.002) showed inverse associations with DQ. We observed opposite directions in the association of DQ for creatinine (for children aged -1 SD: β = -0.05; p =0.01; +1 SD: β = 0.05; p =0.02) and methylhistidine (-1 SD: β = - 0.04; p =0.04; +1 SD: β = 0.04; p =0.03).
Conclusion: Serum biomarkers, including dietary and microbial-derived metabolites involved in the gut-brain axis, may potentially be used to track children at risk for developmental delays.
Funding: Supported by the Brazilian Ministry of Health and the Brazilian National Research Council.
