Validation of the SACOV-19 score for identifying patients at risk of complicated or more severe COVID-19: a prospective study

Abstract

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.

Electronic data capture in resource-limited settings using the lightweight clinical data acquisition and recording system for clinical studies – LCARS-C

“…Missing values in both studies were due to a lack of information in the clinical records or implausible clinical records, but never because of technical problems. Their results were published recently [22], [23]. In the PCC Study, we collected up to 679 variables per participant in baseline visits and several follow-up visits encompassing medical history, current signs and symptoms, laboratory data, several questionnaires, diagnostic procedures, imaging results, specialist consultations, clinical management decisions and smart-watch data.…”