Infection · 2023
Validation of the SACOV-19 score for identifying patients at risk of complicated or more severe COVID-19: a prospective study.
Многоцентровое исследованиеСтатьяНазвание и аннотация: Перевод пока не подготовлен
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Mahajan Ujjwal Mukund, Erber Johanna, Shamsrizi Parichehr, Voit Florian, Vielhauer Jakob, Johlke Anna-Lena, Benesch Christopher, Khaled Najib Ben, Reinecke Felix, Rudi Wolf-Stephan, Klein Matthias, Jakob Carolin, Oswald Marcus, König Rainer, Schulz Christian, Mayerle Julia, Stubbe Hans Christian
Аннотация
PURPOSE: Identification of patients at risk of complicated or more severe COVID-19 is of pivotal importance, since these patients might require monitoring, antiviral treatment, and hospitalization. In this study, we prospectively evaluated the SACOV-19 score for its ability to predict complicated or more severe COVID-19.
METHODS: In this prospective multicenter study, we included 124 adult patients with acute COVID-19 in three German hospitals, who were diagnosed in an early, uncomplicated stage of COVID-19 within 72 h of inclusion. We determined the SACOV-19 score at baseline and performed a follow-up at 30 days.
RESULTS: The SACOV-19 score's AUC was 0.816. At a cutoff of > 3, it predicted deterioration to complicated or more severe COVID-19 with a sensitivity of 94% and a specificity of 55%. It performed significantly better in predicting complicated COVID-19 than the random tree-based SACOV-19 predictive model, the CURB-65, 4C mortality, or qCSI scores.
CONCLUSION: The SACOV-19 score is a feasible tool to aid decision making in acute COVID-19.
METHODS: In this prospective multicenter study, we included 124 adult patients with acute COVID-19 in three German hospitals, who were diagnosed in an early, uncomplicated stage of COVID-19 within 72 h of inclusion. We determined the SACOV-19 score at baseline and performed a follow-up at 30 days.
RESULTS: The SACOV-19 score's AUC was 0.816. At a cutoff of > 3, it predicted deterioration to complicated or more severe COVID-19 with a sensitivity of 94% and a specificity of 55%. It performed significantly better in predicting complicated COVID-19 than the random tree-based SACOV-19 predictive model, the CURB-65, 4C mortality, or qCSI scores.
CONCLUSION: The SACOV-19 score is a feasible tool to aid decision making in acute COVID-19.