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Showing 2 results for Lymphocytes
Cell population data analysis for early diagnosis and prognosis of COVID-19: A Case-Control Study
Priyadarshini Kumaraswamy Rajeswaran , Preethi Muthusamy Sundar, Prasanna Nedungadi Kumar, Karthikeyan Shanmugam,
Volume 19, Issue 3 (5-2025)
Abstract
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.

The importance of neutrophil-to-lymphocyte, platelet-to-lymphocyte, and neutrophil-to-platelet ratios as predictive indicators of severity in COVID-19 Patients
Subaida Adalam Kunnath, Anandan Kalarikal Raghavan, Feroze Moosa , Aneesha Asok Kumar ,
Volume 19, Issue 5 (9-2025)
Abstract
Background: COVID-19 is a global pandemic caused by Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2). Various clinical and hematological findings have been identified that can predict disease severity. This study aims to investigate the roles of the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and neutrophil-to-platelet ratio (NPR) in predicting the severity of COVID-19 infection.
Methods: In this analytical cross-sectional single-center study, after obtaining Ethics Committee clearance, patients with laboratory-confirmed COVID-19 infection admitted during their first two weeks of illness were included. NLR, PLR, and NPR were derived from the CBC reports. These ratios were compared in each clinical category group to assess the severity.
Results: The total number of cases was 160, with a mean age at diagnosis of 56 years. The proportion of males was slightly higher (54.4%) than that of females (45.6%). The proportion of Category C patients (66.9%) was higher than that of Category B (25%) and Category A (8.1%) patients. It was found that NLR, PLR, and NPR ratios had a statistically significant association with severe COVID-19 infection, suggesting they can be used to differentiate between Category C and Category A or B. NLR is a better predictor of the severity of COVID-19 disease than PLR and NPR.
Conclusion: NLR, PLR, and NPR ratios can serve as predictive markers of disease severity in COVID-19 infections. Among these ratios, NLR has the highest predictive value for disease deterioration.

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