Cell population data analysis for early diagnosis and prognosis of COVID-19: A Case-Control Study

Background: Several hematological indicators have been linked to the intensity and course of Coronavirus Disease of 2019 (COVID-19), including platelets, total white blood cell (WBC) count, lymphocytes, neutrophils (as well as the neutrophil-lymphocyte and platelet-lymphocyte ratios), and hemoglobin. The purpose of this study was to assess the utility of cell population data (CPD) of lymphocyte and monocyte parameters in the early diagnosis of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection. Methods: The baseline complete blood count examination was performed for 222 patients with positive results for COVID-19 (case group) and 161 patients with negative results for COVID-19 (control group). Lymphocyte and monocyte CPD were calculated in both groups. The independent t-test was used to compare the mean values between the two groups. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the discriminating capacity of the individual parameters. Results: The analysis revealed that Standard Deviations of Monocyte Volume (SDMV) and Standard Deviations of Lymphocyte Conductivity (SDLC) showed the highest significance in predicting SARS-CoV-2 infection. Moreover, SDMV had a sensitivity of 93.7% and SDLC had a sensitivity of 80.6% at cut-off values of 22.25 and 10.9, respectively. In the case group, 49 of the 222 patients treated in the intensive care units (ICUs) showed a higher SDMV compared with the remaining 173 patients who were asymptomatic, or mildly symptomatic (P-value <0.03). Conclusion: Our study demonstrates that SDMV and SDLC can serve as reliable and cost-effective markers for early prediction of SARS-CoV-2 infection. Furthermore, SDMV shows potential as a prognostic biomarker. These findings highlight the potential utility of CPD parameters in COVID-19 diagnosis and prognosis.