A novel evidence-based algorithm to predict thromboembolism in patients with COVID-19: preliminary data from a single-center cohort

Abstract

Background: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-related disease (COVID-19) is an infectious disease characterized by systemic inflammation, which might enhance baseline thrombotic risk, especially in hospitalized patients. Little is, however, known about predictors of thrombotic complications in patients with COVID-19.

Methods: We prospectively followed up 180 hospitalized COVID-19 patients. Demographics, clinical and laboratory features at presentation and past medical history were tested as predictors of the first thrombotic complication through multivariate Cox regression analysis and a categorical score generated based on the results.

Results: Sixty-four thromboses were recorded in 54 patients, of whom seven with thrombosis on admission and 47 with thrombosis during hospitalization. Patients with thrombosis were mainly Caucasian and diabetic, had marked baseline signs of inflammation and organ damage, lower PaO<inf>2</inf>/FiO<inf>2</inf> ratio, higher D-dimer levels and history of major hemorrhages. The latter three variables were independently associated to thrombotic complications and concurred to a 0-5 score, which accounted for 80% of the total sample variability. Patients with three or more points of the newly generated score were at higher risk for thrombotic complications (HR=4.9, P<0.001). Patients with thrombotic complications were more likely to be admitted to intensive care and/or to die (HR=1.9, P=0.036). Five of 180 patients were diagnosed with disseminated intravascular coagulation and three of them died. Eleven minor and no major bleeding events were observed.

Conclusions: Patients with COVID-19 are at increased risk for thrombosis and might be stratified on admission based on lower Pao2/FiO2 ratio, higher D-dimer levels and history of major hemorrhages.