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 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. 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

COVID-19 vaccines reduce mortality in hospitalized patients with oxygen requirements: Differences between vaccine subtypes: A multicontinental cohort study

The aim of this study was to analyze whether the coronavirus disease 2019 (COVID-19) vaccine reduces mortality in patients with moderate or severe COVID-19 disease requiring oxygen therapy. A retrospective cohort study, with data from 148 hospitals in both Spain (111 hospitals) and Argentina (37 hospitals), was conducted. We evaluated hospitalized patients for COVID-19 older than 18 years with oxygen requirements. Vaccine protection against death was assessed through a multivariable logistic regression and propensity score matching. We also performed a subgroup analysis according to vaccine type. The adjusted model was used to determine the population attributable risk. Between January 2020 and May 2022, we evaluated 21,479 COVID-19 hospitalized patients with oxygen requirements. Of these, 338 (1.5%) patients received a single dose of the COVID-19 vaccine and 379 (1.8%) were fully vaccinated. In vaccinated patients, mortality was 20.9% (95% confidence interval [CI]: 17.9–24), compared to 19.5% (95% CI: 19–20) in unvaccinated patients, resulting in a crude odds ratio (OR) of 1.07 (95% CI: 0.89–1.29; p = 0.41). However, after considering the multiple comorbidities in the vaccinated group, the adjusted OR was 0.73 (95% CI: 0.56–0.95; p = 0.02) with a population attributable risk reduction of 4.3% (95% CI: 1–5). The higher risk reduction for mortality was with messenger RNA (mRNA) BNT162b2 (Pfizer) (OR 0.37; 95% CI: 0.23–0.59; p < 0.01), ChAdOx1 nCoV-19 (AstraZeneca) (OR 0.42; 95% CI: 0.20–0.86; p = 0.02), and mRNA-1273 (Moderna) (OR 0.68; 95% CI: 0.41–1.12; p = 0.13), and lower with Gam-COVID-Vac (Sputnik) (OR 0.93; 95% CI: 0.6–1.45; p = 0.76). COVID-19 vaccines significantly reduce the probability of death in patients suffering from a moderate or severe disease (oxygen therapy).Fil: Huespe, Ivan. Hospital Italiano. Instituto Universitario. Escuela de Medicina; Argentina. Universidad de Buenos Aires. Facultad de Medicina; ArgentinaFil: Ferraris, Augusto. Hospital Italiano. Instituto Universitario. Escuela de Medicina; ArgentinaFil: Lalueza, Antonio. 12 de Octubre University Hospital; EspañaFil: Valdez, Pascual. Hospital General de Agudos Dalmacio Velez Sarsfield ; Gobierno de la Ciudad Autonoma de Buenos Aires;Fil: Peroni, María Leticia. Hospital Italiano. Instituto Universitario. Escuela de Medicina; ArgentinaFil: Cayetti, Luis A.. Hospital Italiano. Instituto Universitario. Escuela de Medicina; ArgentinaFil: Mirofsky, Matias A.. Hospital Municipal Doctor Leónidas Lucero; ArgentinaFil: Boietti, Bruno Rafael. Hospital Italiano. Instituto Universitario. Escuela de Medicina; ArgentinaFil: Gómez Huelgas, Ricardo. Universidad de Málaga; EspañaFil: Casas Rojo, José M.. Infanta Cristina University Hospital; EspañaFil: Antón Santos, Juan M.. Infanta Cristina University Hospital; EspañaFil: Núñez Cortés, Jesús M.. Hospital General Universitario Gregorio Marañón (hosp Gral Univ G. Marañón); EspañaFil: Lumbreras, Carlos. 12 de Octubre University Hospital; España. Universidad Complutense de Madrid; EspañaFil: Ramos Rincón, Jose Manuel. Universidad de Miguel Hernández; EspañaFil: Barrio, Noelia G.. 12 de Octubre University Hospital; España. Universidad Complutense de Madrid; EspañaFil: Pedrera Jiménez, Miguel. 12 de Octubre University Hospital; España. Universidad Complutense de Madrid; EspañaFil: Martin Escalante, María D.. Costa del Sol Hospital; EspañaFil: Ruiz, Francisco R.. Costa del Sol Hospital; EspañaFil: Onieva García, María Á.. Costa del Sol Hospital; EspañaFil: Toso, Carlos R.. Universidad de Buenos Aires. Facultad de Medicina; ArgentinaFil: Risk, Marcelo. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Houssay. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Hospital Italiano. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional E Ingenieria Biomedica.; ArgentinaFil: Klén, Riku. University of Turku; FinlandiaFil: Pollán, Javier A.. Hospital Italiano. Instituto Universitario. Escuela de Medicina; ArgentinaFil: Gómez Varela, David. Universidad de Viena; Austri