The 123 COVID SCORE: A simple and reliable diagnostic tool to predict in-hospital death in COVID-19 patients on hospital admission

• Published in: PLoS ONE 2024, Vol.19 (10), p.e0309922
• Main Authors: Ostrowska, Malgorzata, Kasprzak, Michal, Fabiszak, Tomasz, Gajda, Jacek, Jaje-Rykowska, Natalia, Michalski, Piotr, Moczulska, Beata, Nowek, Paulina, Piasecki, Maciej, Pilaczynska-Cemel, Marta, Podhajski, Przemyslaw, Prudzic, Paulina, Stepniak, Dominika, Swiatkowski, Damian, Zechowicz, Maciej, Gajda, Robert, Gromadzinski, Leszek, Krys, Jacek, Kubica, Aldona, Przybylski, Grzegorz, Szymanski, Pawel, Kubica, Jacek
• Format: Report
• Language: English
• Subjects: Admission and discharge; Care and treatment; Control; Epidemics; Hospital patients; Hospitals; Medical care; Poland; Quality management
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0309922

Independent mortality predictors identified in multivariate logistic regression analysis were used to build the 123 COVID SCORE. Diagnostic performance of the score was evaluated using the area under the receiver-operating characteristic curve (AUROC). Data from 673 COVID-19 patients with median age of 70 years were used to build the score. In-hospital death occurred in 124 study participants (18.4%). The final score is composed of 3 variables that were found predictive of mortality in multivariate logistic regression analysis: (1) age, (2) oxygen saturation on hospital admission without oxygen supplementation and (3) percentage of lung involvement in chest computed tomography (CT). Four point ranges have been identified: 0-5, 6-8, 9-11 and 12-17, respectively corresponding to low (1.5%), moderate (13.4%), high (28.4%) and very high (57.3%) risk of in-hospital death. The 123 COVID SCORE accuracy measured with the AUROC was 0.797 (95% CI 0.757-0.838; p