Daily combined measurement of platelet count and presepsin concentration can predict in-hospital death of patients with severe coronavirus disease 2019 (COVID-19)

Abstract

The purpose of this study was to classify patients with severe COVID-19 into more detailed risk groups using coagulation/fibrinolysis, inflammation/immune response, and alveolar/myocardial damage biomarkers, as well as to identify prognostic markers for these patients. These biomarkers were measured every day for eight intensive care unit days in 54 adult patients with severe COVID-19. The patients were classified into survivor (n = 40) and non-survivor (n = 14) groups. Univariate and multivariate analyses showed that the combined measurement of platelet count and presepsin concentrations may be the most valuable for predicting in-hospital death, and receiver operating characteristic curve analysis further confirmed this result (area under the curve = 0.832). Patients were consequently classified into three groups (high-, medium-, and low-risk) on the basis of their cutoff values (platelet count 53 × 103/µL, presepsin 714 pg/mL). The Kaplan–Meier curve for 90-day survival by each group showed that the 90-day mortality rate significantly increased as risk level increased (P < 0.01 by the log-rank test). Daily combined measurement of platelet count and presepsin concentration may be useful for predicting in-hospital death and classifying patients with severe COVID-19 into more detailed risk groups.