Sat, Jul 26, 2025
Priyadarshini Kumaraswamy Rajeswaran1 
, Preethi Muthusamy Sundar2 , Prasanna Nedungadi Kumar2 , Karthikeyan Shanmugam2
, Preethi Muthusamy Sundar2 , Prasanna Nedungadi Kumar2 , Karthikeyan Shanmugam2
1- PSG Institute of Medical Sciences and Research , drpriyadarshini.kr@gmail.com
2- PSG Institute of Medical Sciences and Research
2- PSG Institute of Medical Sciences and Research
Abstract: (93 Views)
Background and Objectives: Several haematological indicators have been linked to the intensity and course of COVID-19 infection, including platelets, white blood cell total 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 lymphocytes and monocytes parameters in the early diagnosis of SARS-CoV-2 infection.
Methods: The baseline complete blood count examination for 222 patients with proven COronaVIrus Disease of 2019(COVID-19) (case group) and 161 patients with negative for COVID-19 investigations (control group). Lymphocyte and monocyte CPD were calculated in both the groups. The independent t-test was used to compare the mean values between the two groups Receiver operating characteristic analysis was performed to evaluate the discriminating capacity of the individual parameters.
Results: The analysis revealed that Standard Deviations of Monocyte Volume (SDMV) and Lymphocyte Conductivity (SDLC) showed highest significance in predicting SARS-CoV-2 infection. 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 were treated in the intensive care unit showed higher SDMV when 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.
Methods: The baseline complete blood count examination for 222 patients with proven COronaVIrus Disease of 2019(COVID-19) (case group) and 161 patients with negative for COVID-19 investigations (control group). Lymphocyte and monocyte CPD were calculated in both the groups. The independent t-test was used to compare the mean values between the two groups Receiver operating characteristic analysis was performed to evaluate the discriminating capacity of the individual parameters.
Results: The analysis revealed that Standard Deviations of Monocyte Volume (SDMV) and Lymphocyte Conductivity (SDLC) showed highest significance in predicting SARS-CoV-2 infection. 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 were treated in the intensive care unit showed higher SDMV when 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.
References
1. Zhu Z, Cai T, Fan L, Lou k, Hua X, Huang Z, et al. Clinical value of immune-inflammatory parameters to assess the severity of coronavirus disease 2019. Int J Infect Dis. 2020;95:332-9. [View at Publisher] [DOI] [PMID] [Google Scholar]
2. Zhu Y, Cao X, Tao G, Xie W, Hu Z, Xu D. The lymph index: a potential hematological parameter for viral infection. Int J Infect Dis. 2013;17(7):e490-e493. [View at Publisher] [DOI] [PMID] [Google Scholar]
3. Shrivastava V, Ahmad S, Mittal G, Gupta V, Shirazi N, Kalra V. Evaluation of haematological and volume, conductivity and scatter parameters of leucocytes for aetiological diagnosis of undifferentiated fevers. Trans R Soc Trop Med Hyg. 2017;111(12):546-54. [View at Publisher] [DOI] [PMID] [Google Scholar]
4. Choccalingam C. Volume, conductance, and scatter parameters of neoplastic and nonneoplastic lymphocytes using Coulter LH780. J Lab Physicians. 2018;10(1):85-8. [View at Publisher] [DOI] [PMID] [Google Scholar]
5. Zeng X, Xing H, Wei Y, Tang Z, Lu X, Wang Z, et al. Monocyte volumetric parameters and lymph index are increased in SARS-CoV-2 infection.Int J Lab Hematol. 2020;42(6):266-9. [View at Publisher] [DOI] [PMID] [Google Scholar]
6. Arora P, Gupta PK, Lingaiah R, Mukhopadhyay AK. Volume, conductivity, and scatter parameters of leukocytes as early markers of sepsis and treatment response. Journal of Laboratory Physicians. 2019 ;11(1):29-33 [View at Publisher] [DOI] [PMID] [Google Scholar]
7. Zhou N, Liu L, Li D, Zeng Q, Song X. VCS parameters of neutrophils, monocytes and lymphocytes may indicate local bacterial infection in cancer patients who accepted cytotoxic chemotherapeutics. Eur J Clin Microbiol Infect Dis. 2016;35(1):41-8. [View at Publisher] [DOI:10.1007/s10096-015-2499-2] [PMID] [Google Scholar]
8. Nesargi P, Niranjan HS, Bandiya P, Benakappa N. Neutrophil Volume, conductivity and scatter (VCS) as a screening tool in neonatal sepsis. Sci Rep. 2020;10(1):4457 [View at Publisher] [DOI] [PMID] [Google Scholar]
9. Chaves F, Tierno B, Xu D. Quantitative determination of neutrophil VCS parameters by the Coulter automated hematology analyzer: new and reliable indicators for acute bacterial infection. Am J Clin Pathol. 2005;124(3):440-4. [View at Publisher] [DOI] [PMID] [Google Scholar]
10. Kannan A, Selvam P. The potential of using VCS parameters of neutrophils and monocytes as an early diagnostic tool in acute bacterial infections. Nat J Lab Med. 2017;6(2)-38-43. [View at Publisher] [Google Scholar]
11. RAI S, SINGH S, PHILIPOSE CS, MENDONCA BS, BASAVARAJU VK. Utility of DxH 800 VCS Parameters and Lymph Index in Predicting Dengue. Journal of Clinical & Diagnostic Research. 2019;13(8). [View at Publisher] [DOI] [Google Scholar]
12. Rajeswaran PK, Kumar PN, Shanmugam K. The Application of Automated Cell Population Data for Early Diagnosis of Dengue Fever. International Journal of Advanced Medical and Health Research. 2023;10(1):27-31. [View at Publisher] [DOI] [Google Scholar]
13. Ognibene A, Lorubbio M, Magliocca P, Tripodo E, Vaggelli G, Iannelli G, et al. Elevated monocyte distribution width in COVID-19 patients: The contribution of the novel sepsis indicator. Clin Chim Acta. 2020;509:22-4. [View at Publisher] [DOI] [PMID] [Google Scholar]
14. Naoum FA, Ruiz ALZ, Martin FHO, Brito THG, Hassem V, Oliveira MGL. Diagnostic and prognostic utility of WBC counts and cell population data in patients with COVID-19. Int J Lab Hematol. 2021;43(S1):124-8. [View at Publisher] [DOI] [PMID] [Google Scholar]
15. Zeng X, Xing H, Wei Y, Tang Z, Lu X, Wang Z, et al. Monocyte volumetric parameters and lymph index are increased in SARS-CoV-2 infection. Int J Lab Hematol. 2020;42(6):e266-e9. [View at Publisher] [DOI] [PMID] [Google Scholar]
16. Vasse M, Ballester MC, Ayaka D, Sukhachev D, Delcominette F, Habarou F, et al. Interest of the cellular population data analysis as an aid in the early diagnosis of SARS-CoV-2 infection. Int J Lab Hematol.2021 ;43(1):116-22. [View at Publisher] [DOI] [PMID] [Google Scholar]
17. Vasse M, Sukhachev D, Ballester MC, Delcominette F, Mellot F, Habarou F, et al. Prognostic value of cellular population data in patients with COVID-19. Inform Med Unlocked. 2023;38:101207. [View at Publisher] [DOI] [PMID] [Google Scholar]
18. Singh J, Yadav AK, Pakhare A, Kulkarni P, Lokhande L, Soni P, et al. Comparative analysis of the diagnostic performance of five commercial COVID-19 qRT PCR kits used in India. Sci Rep. 2021:11(1):22013. [View at Publisher] [DOI] [PMID] [Google Scholar]
19. Richardson S, Hirsch JS, Narasimhan M, Crawford JM, McGinn T, Davidson KW. Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area. JAMA 2020;323(20): 2052-9. [View at Publisher] [DOI] [PMID] [Google Scholar]
20. Kala M, Ahmad S, Dhebane M, Das K, Raturi M, Tyagi M, et al. A Cross-Sectional Comparative Characterization of Hematological Changes in Patients with COVID-19 Infection, Non-COVID Influenza-like Illnesses and Healthy Controls. Viruses. 2023;15(1):134. [View at Publisher] [DOI] [PMID] [Google Scholar]
21. Terpos E, Ntanasis-Stathopoulos I, Elalamy I, Kastritis E, Sergentanis TN, Politou M, et al. Hematological findings and complications of COVID-19. Am J Hematol. 2020;95(7):834-47. [View at Publisher] [DOI] [PMID] [Google Scholar]
22. Sun S, Cai X, Wang H, He G, Lin Y, Lu B, et al. Abnormalities of peripheral blood system in patients with COVID-19 in Wenzhou, China. Clin Chim Acta. 2020;507:174-80. [View at Publisher] [DOI] [PMID] [Google Scholar]
23. Violetis OA, Chasouraki AM, Giannou AM, Baraboutis IG. COVID-19 Infection and Haematological Involvement: a Review of Epidemiology, Pathophysiology and Prognosis of Full Blood Count Findings. SN Compr Clin Med. 2020;2(8):1089-93. [View at Publisher] [DOI] [PMID] [Google Scholar]
24. Li Q, Ding X, Xia G, Chen HG, Chen F, Geng Z. et al. Eosinopenia and elevated C-reactive protein facilitate triage of COVID-19 patients in fever clinic: A retrospective case-control study. EClinicalMedicine. 22020:23:100375. [View at Publisher] [DOI] [PMID] [Google Scholar]
25. Xia Z. Eosinopenia as an early diagnostic marker of COVID-19 at the time of the epidemic. EClinicalMedicine. 2020;23:100398. [View at Publisher] [DOI] [PMID] [Google Scholar]
26. Soni M. Evaluation of eosinopenia as a diagnostic and prognostic indicator in COVID-19 infection. Int J Lab Hematol. 2021:43 Suppl 1:137-41. [View at Publisher] [DOI] [PMID] [Google Scholar]
27. Mardani R, Ahmadi Vasmehjani A, Zali F, Gholami A, Mousavi Nasab SD, et al. Laboratory Parameters in Detection of COVID-19 Patients with Positive RT-PCR; a Diagnostic Accuracy Study. Arch Acad Emerg Med. 2020;8(1):e43. [View at Publisher] [DOI] [PMID] [Google Scholar]
28. Sehanobish E, Barbi M, Fong V, Kravitz M, Sanchez Tejera D, Asad M, et al. COVID-19-induced anosmia and ageusia are associated with younger age and lower blood eosinophil counts. Am J Rhinol Allergy. 2021;35(6):830-9. [View at Publisher] [DOI] [PMID] [Google Scholar]
29. Ponti G, Maccaferri M, Ruini C, Tomasi A, Ozben T. Biomarkers associated with COVID-19 disease progression. Crit Rev Clin Lab Sci. 2020;57(6):389-99. [View at Publisher] [DOI] [PMID] [Google Scholar]
30. Yan Q, Li P, Ye X, Huang X, Mo X, Wang Q, et al. Longitudinal peripheral blood transcriptional analysis of COVID-19 patients captures disease progression and reveals potential biomarkers. MedRxiv. 2020:2020-05. [View at Publisher] [DOI] [Google Scholar]
31. Lapić I, Brenčić T, Rogić D, Lukić M, Lukić I, Kovačić M, et al. Cell population data: Could a routine hematology analyzer aid in the differential diagnosis of COVID-19? Int J Lab Hematol. 2021;43(2):e64-e7. [View at Publisher] [DOI] [PMID] [Google Scholar]
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