The Role of Platelet Parameters in Predicting the Disease Severity of COVID-19 Patients: A Hospital-Based Study

Background and objective Globally, a large number of people have been impacted by the extremely contagious coronavirus disease 2019 (COVID-19) infection, and several pieces of literature were published on hematological parameter changes in this infection, particularly focusing on leucocytes. In this study, we have analyzed the platelet parameters and platelet-leucocyte ratios in COVID-19 patients and correlated them with the disease severity. Methods The COVID-19 patients who were hospitalized during the second peak of the pandemic were assessed. The platelet count and indices, platelet to lymphocyte ratio (PLR), neutrophil to platelet ratio (NPR), and clinical severity of each patient were analyzed. The significance of parameters and clinical severity was evaluated using analysis of variance (ANOVA) and the Kruskal Wallis test. A bivariate analysis was performed to assess the strength of the association. Receiver operating characteristic (ROC) curves were plotted to detect the predictive value of parameters for disease severity. Results The data of 132 COVID-19 patients has been evaluated. The average mean age was 45.60 ± 15.76 years with slight female predominance. Thrombocytopenia was found in 33% of cases with the majority of them being mild. Age, platelet distribution width (PDW), and PLR and NPR parameters were significantly (p-value <0.05) associated with disease severity. ROC curves showed age, PDW, PLR, NPR, absolute neutrophil count (ANC), and absolute lymphocyte count (ALC) had significant prediction values for clinical severity. Conclusions Platelet parameters may not accurately reflect the severity of the disease, but when combined with leucocyte parameters and their ratios (PLR and NPR), they offer important information about disease severity.