Predicting of poor outcomes in COVID-19 patients: Experience from an Argentinean hospital

Abstract

Introduction: The pressure over health systems caused by the COVID-19 pandemic brought about the need to develop tools that would allow for the identification of those patients that require immediate attention. Our objective was to identify clinical and biochemical predictors of poor outcomes (PO) in a cohort of patients hospitalized due to COVID-19 in an Argentinean public hospital. Methods: Prospective cohort study conducted from March 3rd, 2020 to February 16th, 2021 in a tertiary care center in Santa Fe, Argentina. Clinical and biochemical characteristics of patients with COVID-19 pneumonia admitted consecutively were analyzed in order to identify predictors of a composite of poor outcomes (PO) -all-cause mortality and/or need for invasive mechanical ventilation. Results: 421 patients were included. The mean age was 56.13 ± 15.05 years. 57.0% were males. 79.7% presented at least one comorbidity. 27.7% (n=116) presented PO. In the multivariate analysis, a higher 4C-score and a higher LDH, as well as a lower SatO2/FiO2, were associated with a higher risk of PO. No variable reached an AUC of 0.800 in the ROC analysis. 4C-score presented a numerically higher AUC (0.766 IC 95% 0.715-0.817). Conclusions: Each point that the 4C-score increases, the risk of PO rises by 28%. Also, for every 100-units increase in LDH or 50-units decrease in SatO2/FiO2 at admission, there is a 20% increased risk of PO.