Platelet-Based Biomarkers for Diagnosis and Prognosis in COVID-19 Patients

Abstract

Coronavirus disease 2019 (COVID-19) caused millions of deaths worldwide. COVID-19’s clinical manifestations range from no symptoms to a severe acute respiratory syndrome, which can result in multiple organ failure, sepsis, and death. Severe COVID-19 patients develop pulmonary and extrapulmonary infections, with a hypercoagulable state. Several inflammatory or coagulatory biomarkers are currently used with predictive values for COVID-19 severity and prognosis. In this manuscript, we investigate if a combination of coagulatory and inflammatory biomarkers could provide a better biomarker with predictive value for COVID-19 patients, being able to distinguish between patients that would develop a moderate or severe COVID-19 and predict the disease outcome. We investigated 306 patients with COVID-19, confirmed by severe acute respiratory syndrome coronavirus 2 RNA detected in the nasopharyngeal swab, and retrospectively analyzed the laboratory data from the first day of hospitalization. In our cohort, biomarkers such as neutrophil count and neutrophil-to-lymphocyte ratio from the day of hospitalization could predict if the patient would need to be transferred to the intensive care unit but failed to identify the patients´ outcomes. The ratio between platelets and inflammatory markers such as creatinine, C-reactive protein, and urea levels is associated with patient outcomes. Finally, the platelet/neutrophil-to-lymphocyte ratio on the first day of hospitalization can be used with predictive value as a novel severity and lethality biomarker in COVID-19. These new biomarkers with predictive value could be used routinely to stratify the risk in COVID-19 patients since the first day of hospitalization.

Keywords

• COVID-19
• SARS-CoV-2
• platelet
• coagulation
• thrombocytopenia
• inflammation