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

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.

COVID-19: The Development and Validation of a New Mortality Risk Score

“…The results of the comparative analysis of the ROC curves of our CZ-COVID-19 Score versus other COVID-19 scoring systems for the 388 patients in the derivation cohort are shown in Table 3. The CZ-COVID-19 Score with its AUC = 0.924, CI 95% 0.893-0.948 performed better than all the following other scores considered: Charlson Comorbidity Index (CCI) [10]; Pneumonia Severity Index (PSI) [12]; National Early Warning Score (NEWS) on admission [11]; International Severe Acute Respiratory Infection Consortium-Coronavirus Clinical Characterisation Consortium (ISARIC 4C) [16]; Hospitalisation or Outpatient Management of Patients with SARS-CoV-2 (HOME-CoV) [17]; ABC2-SPH risk score (ABC2-SPH) [18]; CAPS-D score [19]; SOARS score abbreviated for SpO 2 , obesity, age, respiratory rate, stroke history (SOARS) [20], COVID-19 severity index [21], ASCL score abbreviated for age, sex, CRP at hospital admission, and LDH at hospital admission (ASCL) [22]; COVID-19 Early Warning Score (COEWS) [23]; National Early Warning Score 2 Plus (NEWS 2 Plus) [24] (Table 3).…”