The use of 8-diff clinical blood testing of patients to assess the severity of the new coronavirus infection

Introduction. A new coronavirus infection causes a variety of changes in the body of an infected person, which can be monitored using clinical blood analysis. The capabilities of flow cytometry allow to expanding the range of analyzed cell populations, which gives a more complete picture of the patient’s condition and the course of infection process.

Aim. To study the extended 8-diff clinical blood analysis in patients with COVID-19 and to identify the parameters characterizing a severe course and an unfavorable outcome.

Material and Methods. The study group comprised 282 patients with a confirmed diagnosis of a new coronavirus infection. The following parameters of the extended 8-diff clinical blood test were evaluated: the total content of leukocytes and their populations, the number of reactive and antibody-synthesizing lymphocytes (RE-LYMPH, AS-LYMPH), indicators characterizing the reactivity and granularity of neutrophils (NEUT-RI, NEUT-GI), erythrocyte count, hemoglobin level, normoblast count, and platelet count. Statistical data were processed using the Statistica 10.0 software.

Results. The blood picture of patients with a severe course of COVID-19 as well as of those with an unfavorable outcome of disease was characterized by neutrophilia, normoblastemia, and an increase in the number of immature granulocytes. At the same time, there was a significant decrease in the number of lymphocytes and monocytes below the reference interval and a decrease in the number of eosinophils to the extent of complete absence. The performed logistic regression analysis allowed to determine the most significant hematological parameters in predicting the outcome of COVID-19 as follows: the total number of leukocytes (OR 1.3), neutrophils (OR 2.1), reactive neutrophils (OR 1.3), eosinophils (OR 0.05), monocytes (OR 0.2), lymphocytes (OR 0.4), and neutrophil-to-lymphocyte ratio (NLR) (OR 1.4). Also, the threshold values were established for these parameters as follows: the total number of leukocytes > 7.2 × 10⁹/L, neutrophils > 5 × 10⁹/L, reactive neutrophils > 48.6 Fi, eosinophils < 0.05 × 10⁹/L, lymphocytes < 1.3 × 10⁹/L, monocytes < 0.5 × 10⁹/L, and NLR > 2.9 were associated with an unfavorable outcome of the disease.

Conclusion. The obtained data may be used for a comprehensive evaluation of COVID-19 patient condition along with other laboratory markers of the severe course of the infection.

1. Bazdyrev E.D. Coronavirus disease: A global problem of the 21st century. Complex Problems of Cardiovascular Diseases. 2020;9(2):6–16. (In Russ.). DOI: 10.17802/2306-1278-2020-9-2-6-16.

2. Santotoribio J.D., Nuñez-Jurado D., Lepe-Balsalobre E. Evaluation of routine blood tests for diagnosis of suspected coronavirus disease 2019. Clin. Lab. 2020;66(9). DOI: 10.7754/Clin.Lab.2020.200522.

3. Gibson P.G., Qin L., Puah S.H. COVID-19 acute respiratory distress syndrome (ARDS): clinical features and differences from typical preCOVID-19 ARDS. Med. J. Aust. 2020;213(2):54–56.e1. DOI: 10.5694/mja2.50674.

4. Zheng Y., Zhang Y., Chi H., Chen S., Peng M., Luo L. et al. The hemocyte counts as a potential biomarker for predicting disease progression in COVID-19: A retrospective study. Clin. Chem. Lab. Med. 2020;58(7):1106–1115. DOI: 10.1515/cclm-2020-0377.

5. Kwiecień I., Rutkowska E., Kulik K., Kłos K., Plewka K., Raniszewska A. .et al. Neutrophil maturation, reactivity and granularity research parameters to characterize and differentiate convalescent patients from active SARS-CoV-2 infection. Cells. 2021;10(9):2332. DOI: 10.3390/cells10092332.

6. Leppkes M., Knopf J., Nashberger E., Lindemann A., Singh J., Herrmann I. et al. Vascular occlusion with neutrophil extracellular traps in COVID-19. EBioMedicine. 2020;58:102925. DOI: 10.1016/j.ebiom.2020.102925.

7. Yang L., Liu S., Liu J., Zhang Z., Wan X., Huang B. et al. COVID-19: Immunopathogenesis and Immunotherapeutics. Signal Transduct. Target. Ther. 2020;5(1):128. DOI: 10.1038/s41392-020-00243-2.

8. Cabrera L.E., Pekkarinen P.T., Alander M., Nowlan K.H.A., Nguyen N.A., Jokiranta S. et al. Characterization of low growth granulocytes in COVID-19. PLoS Pathogens. 2021;17(7):e1009721. DOI: 10.1371/journal.ppat.1009721.

9. Tanni F., Akker E., Zaman M.M., Figueroa N., Tharian B., Hupart K.H. Eosinopenia and COVID-19. J. Am. Osteopath. Assoc. 2020;120(8):504– 508.

10. Bass D.A. Behavior of eosinophil leukocytes in acute inflammation. II. Eosinophil dynamics during acute inflammation. J. Clin. Invest. 1975;56(4):870–9. DOI: 10.7556/jaoa.2020.091.

11. Pan F., Yang L., Li Y., Liang B., Li L., Ye T. et al. Factors associated with mortality in patients with severe coronavirus disease-19 (COVID-19): A case-control study. Int. J. Med. Sci. 2020;17(9):1281–1292. DOI: 10.7150/ijms.46614.

12. Dandekar A.A., Perlman S. Immunopathogenesis of coronavirus infections: Implications for SARS. Nat. Rev. Immunol. 2005;5(12):917–927. DOI: 10.1038/nri1732.

13. Gu J., Gong E., Zhang B., Zheng J., Gao Z., Zhong Y. et al. Multiple organ infection and the pathogenesis of SARS. J. Exp. Med. 2005;202(3):415– 424. DOI: 10.1084/jem.20050828.

14. Yarilin А.А. Immunology: Textbook. Moscow: GEOTAR-Media; 2010:752. (In Russ.).

15. Martens R. J.H., van Adrichem A.J., Mattheij N.J.A., Brouwer C.G., van Twist D.J.L., Broerse J.J.C.R. et al. Hemocytometric characteristics of COVID-19 patients with and without cytokine storm syndrome on the Sysmex XN-10 hematology analyzer. Clin. Chem. Lab. Med. 2021;59(4):783–793. DOI: 10.1515/cclm-2020-1529.

16. Bläckberg A., Fernström N., Sarbrant E., Rasmussen M., Sunnerhagen T. Antibody kinetics and clinical course of COVID-19 a prospective observational study. PLoS One. 2021;16(3):e0248918. DOI: 10.1371/journal.pone.0248918.

17. Knoll R., Schultze J.L., Schulte-Schlepping J. Monocytes and macrophages in COVID-19. Front. Immunol. 2021;12:720109. DOI: 10.3389/ fimmu.2021.720109.

18. Zhou Y., Fu B., Zheng X., Wang D., Zhao C., Qi Y. et al. Pathogenic T-cells and inflammatory monocytes incite inflammatory storms in severe COVID-19 patients. Natl. Sci. Rev. 2020;7(6):998–1002. DOI: 10.1093/nsr/nwaa041.

19. Erdogan A., Can F.E., Gönüllü H. Evaluation of the prognostic role of NLR, LMR, PLR, and LCR ratio in COVID-19 patients. J. Med. Virol. 2021;93(9):5555–5559. DOI: 10.1002/jmv.27097.

20. Constantino B.T., Kogionis B. Nuclear RBCs-Significance in a peripheral blood film. Laboratory Medicine. 2000;31(4):223–229.

21. Kuert S., Holland-Letz T., Friese J., Stachon A. Association of nucleated red blood cells in blood and arterial oxygen partial tension. Clin. Chem. Lab. Med. 2011;49(2):257–263. DOI: 10.1515/CCLM.2011.041.

22. Linssen J., Ermens A., Berrevoets M., Seghezzi M., Previtali G., van der Sar-van der Brugge S. et al. A novel haemocytometric COVID-19 prognostic score developed and validated in an observational multicentre European hospital-based study. Elife. 2020;9:e63195. DOI: 10.7554/eLife.63195.