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

  1. Riku Klén
  2. Ivan A Huespe  Is a corresponding author
  3. Felipe Aníbal Gregalio
  4. Antonio Lalueza Lalueza Blanco
  5. Miguel Pedrera Jimenez
  6. Noelia Garcia Barrio
  7. Pascual Ruben Valdez
  8. Matias A Mirofsky
  9. Bruno Boietti
  10. Ricardo Gómez-Huelgas
  11. José Manuel Casas-Rojo
  12. Juan Miguel Antón-Santos
  13. Javier Alberto Pollan
  14. David Gómez-Varela  Is a corresponding author
  1. University of Turku, Finland
  2. Hospital Italiano de Buenos Aires, Argentina
  3. Hospital Universitario 12 De Octubre, Spain
  4. Vélez Sarsfield Hospital, Argentina
  5. Hospital Municipal de Agudos Dr Leónidas Lucero, Argentina
  6. University of Malaga, Spain
  7. Infanta Cristina University Hospital, Spain
  8. 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

  1. Riku Klén

    Turku PET Centre, University of Turku, Turku, Finland
    Competing interests
    The authors declare that no competing interests exist.
  2. Ivan A Huespe

    Hospital Italiano de Buenos Aires, Buenos Aires, Argentina
    For correspondence
    ivan.huespe@hospitalitaliano.org.ar
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3445-6981
  3. Felipe Aníbal Gregalio

    Hospital Italiano de Buenos Aires, Buenos Aires, Argentina
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3189-2382
  4. Antonio Lalueza Lalueza Blanco

    Internal Medicine Department, Hospital Universitario 12 De Octubre, Madrid, Spain
    Competing interests
    The authors declare that no competing interests exist.
  5. Miguel Pedrera Jimenez

    Data Science Unit, Hospital Universitario 12 De Octubre, Madrid, Spain
    Competing interests
    The authors declare that no competing interests exist.
  6. Noelia Garcia Barrio

    Data Science Unit, Hospital Universitario 12 De Octubre, Madrid, Spain
    Competing interests
    The authors declare that no competing interests exist.
  7. Pascual Ruben Valdez

    Vélez Sarsfield Hospital, Buenos Aires, Argentina
    Competing interests
    The authors declare that no competing interests exist.
  8. Matias A Mirofsky

    Hospital Municipal de Agudos Dr Leónidas Lucero, Bahía Blanca, Argentina
    Competing interests
    The authors declare that no competing interests exist.
  9. Bruno Boietti

    Hospital Italiano de Buenos Aires, Buenos Aires, Argentina
    Competing interests
    The authors declare that no competing interests exist.
  10. Ricardo Gómez-Huelgas

    Internal Medicine Department, University of Malaga, Màlaga, Spain
    Competing interests
    The authors declare that no competing interests exist.
  11. José Manuel Casas-Rojo

    Internal Medicine Department, Infanta Cristina University Hospital, Madrid, Spain
    Competing interests
    The authors declare that no competing interests exist.
  12. Juan Miguel Antón-Santos

    Internal Medicine Department, Infanta Cristina University Hospital, Madrid, Spain
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3443-1100
  13. Javier Alberto Pollan

    Hospital Italiano de Buenos Aires, Buenos Aires, Argentina
    Competing interests
    The authors declare that no competing interests exist.
  14. David Gómez-Varela

    Department of Pharmaceutical Sciences, University of Vienna, Vienna, Austria
    For correspondence
    david.gomez.varela@univie.ac.at
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2502-9419

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.

Reviewing Editor

  1. Evangelos J Giamarellos-Bourboulis, National and Kapodistrian University of Athens, Medical School, Greece

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).

Version history

  1. Received: February 2, 2023
  2. Accepted: August 23, 2023
  3. Accepted Manuscript published: August 24, 2023 (version 1)
  4. Version of Record published: September 5, 2023 (version 2)

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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  1. Riku Klén
  2. Ivan A Huespe
  3. Felipe Aníbal Gregalio
  4. Antonio Lalueza Lalueza Blanco
  5. Miguel Pedrera Jimenez
  6. Noelia Garcia Barrio
  7. Pascual Ruben Valdez
  8. Matias A Mirofsky
  9. Bruno Boietti
  10. Ricardo Gómez-Huelgas
  11. José Manuel Casas-Rojo
  12. Juan Miguel Antón-Santos
  13. Javier Alberto Pollan
  14. David Gómez-Varela
(2023)
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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https://doi.org/10.7554/eLife.85618

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