Thu, Sep 12, 2024
Volume 16, Issue 6 (Special issue (Nov-Dec) 2022)
mljgoums 2022, 16(6): 35-39 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Jaykar H, Nagare M, Bhat G. Evaluation of Absolute Neutrophil Count in COVID-19 Patients in a Tertiary Care Hospital. mljgoums 2022; 16 (6) :35-39
URL: http://mlj.goums.ac.ir/article-1-1522-en.html
URL: http://mlj.goums.ac.ir/article-1-1522-en.html
1- Department of Pathology, Maharashtra Institute of Medical Education and Research, Medical College, Talegaon Dabhade, Pune, Maharashtra, India , dr.harshaj@gmail.com
2- Department of Pathology, Maharashtra Institute of Medical Education and Research, Medical College, Talegaon Dabhade, Pune, Maharashtra, India
3- Department of Pathology, Maharashtra Institute of Medical Education and Research, Medical College, Talegaon Dabhade, Pune, Maharashtra, India
2- Department of Pathology, Maharashtra Institute of Medical Education and Research, Medical College, Talegaon Dabhade, Pune, Maharashtra, India
3- Department of Pathology, Maharashtra Institute of Medical Education and Research, Medical College, Talegaon Dabhade, Pune, Maharashtra, India
Full-Text [PDF 407 kb]
(384 Downloads)
| Abstract (HTML) (1123 Views)
.PNG)
Full-Text: (529 Views)
INTRODUCTION
Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2), which affects the lower respiratory tract. The clinical manifestations of the disease range from mild symptoms to severe illness, causing morbidity and mortality. Originating in Wuhan, China, COVID-19 rapidly spread across the world and turned into a pandemic, resulting in considerable human and economic loss (1, 2). Advanced age, male gender, and pre-existing comorbidities have been linked with increased disease severity (3-5). In severe patients, neutrophil count in blood is increased significantly. In COVID-19, hyper-inflammatory and immune thrombotic responses cause lung damage, thrombosis, fibrosis, and severe pneumonia resulting in respiratory failure (6, 7). It has been reported that inflammation biomarkers including D-dimer, interleukin-6 (IL-6), ferritin, and C-reactive protein along with neutrophil-lymphocyte ratio (NLR) are elevated in the early stages of SARS-CoV-2 infection (8-12). This study aimed to evaluate absolute neutrophil count (ANC) and morphological changes of neutrophils including segmentation, pseudo-Pelger–Huët (PHA), hypolobation, pyknotic nuclei, abnormal granularity, and cytoplasmic vacuolation in peripheral blood smears of COVID-19 patients.
MATERIALS AND METHODS
This retrospective, cross-sectional study was carried out on patients admitted to the outpatient department of OBGY Rural Hospital (Maharashtra, India) from April 2021 to June 2021. The minimum sample size was estimated at 144 according to the following formula and considering a prevalence rate of 40% (8), 95% confidence interval, and 10% error:
N= (S.D)2 x Zα2 (Diff) 2.
Inclusion criteria were having a positive reverse transcription polymerase chain reaction (RT-PCR) test for COVID-19 and willingness to participate in the study. Those aged less than 18 years and with pre-existing renal or vascular diseases, seizure disorders, severe anemia, and liver disease were excluded from the study. Overall, 143 patients with COVID-19 and 143 healthy subjects (with a negative RT-PCR for COVID-19) were enrolled in the study. Written informed consent was taken from all subjects. Ethics approval was also obtained from the Institutional Ethics Committee (Approval code: no.IEC/MIMER/2022/784).
A peripheral venous blood sample (3 ml) was taken from all subjects under aseptic precautions. The blood samples were collected in EDTA vacutainers and then transferred to the laboratory. The samples were analyzed using a fully automated blood cell counter for the estimation of complete blood count. A peripheral blood smear was prepared and stained with Leishman stain.
Data were analyzed using the SPSS software (version 26) at a statistical significance of 0.05.
RESULTS
The age-wise distribution of COVID-19 patients is presented in table 1. Most patients were in the age range of 61-75 years and 31-45 years.
Table 1- Age-wise distribution of COVID-19 patients
Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2), which affects the lower respiratory tract. The clinical manifestations of the disease range from mild symptoms to severe illness, causing morbidity and mortality. Originating in Wuhan, China, COVID-19 rapidly spread across the world and turned into a pandemic, resulting in considerable human and economic loss (1, 2). Advanced age, male gender, and pre-existing comorbidities have been linked with increased disease severity (3-5). In severe patients, neutrophil count in blood is increased significantly. In COVID-19, hyper-inflammatory and immune thrombotic responses cause lung damage, thrombosis, fibrosis, and severe pneumonia resulting in respiratory failure (6, 7). It has been reported that inflammation biomarkers including D-dimer, interleukin-6 (IL-6), ferritin, and C-reactive protein along with neutrophil-lymphocyte ratio (NLR) are elevated in the early stages of SARS-CoV-2 infection (8-12). This study aimed to evaluate absolute neutrophil count (ANC) and morphological changes of neutrophils including segmentation, pseudo-Pelger–Huët (PHA), hypolobation, pyknotic nuclei, abnormal granularity, and cytoplasmic vacuolation in peripheral blood smears of COVID-19 patients.
MATERIALS AND METHODS
This retrospective, cross-sectional study was carried out on patients admitted to the outpatient department of OBGY Rural Hospital (Maharashtra, India) from April 2021 to June 2021. The minimum sample size was estimated at 144 according to the following formula and considering a prevalence rate of 40% (8), 95% confidence interval, and 10% error:
N= (S.D)2 x Zα2 (Diff) 2.
Inclusion criteria were having a positive reverse transcription polymerase chain reaction (RT-PCR) test for COVID-19 and willingness to participate in the study. Those aged less than 18 years and with pre-existing renal or vascular diseases, seizure disorders, severe anemia, and liver disease were excluded from the study. Overall, 143 patients with COVID-19 and 143 healthy subjects (with a negative RT-PCR for COVID-19) were enrolled in the study. Written informed consent was taken from all subjects. Ethics approval was also obtained from the Institutional Ethics Committee (Approval code: no.IEC/MIMER/2022/784).
A peripheral venous blood sample (3 ml) was taken from all subjects under aseptic precautions. The blood samples were collected in EDTA vacutainers and then transferred to the laboratory. The samples were analyzed using a fully automated blood cell counter for the estimation of complete blood count. A peripheral blood smear was prepared and stained with Leishman stain.
Data were analyzed using the SPSS software (version 26) at a statistical significance of 0.05.
RESULTS
The age-wise distribution of COVID-19 patients is presented in table 1. Most patients were in the age range of 61-75 years and 31-45 years.
Table 1- Age-wise distribution of COVID-19 patients
| Age range (years) | Number of COVID-19 cases | Percent | |
| 16-30 | 24 | 16.7 | |
| 31-45 | 40 | 28 | |
| 46-60 | 30 | 21 | |
| 61-75 | 44 | 30.7 | |
| 76-90 | 05 | 3.49 | |
| Total | 143 | 100 |
As shown in table 2, the ANC of COVID-19 patients was significantly higher than that of healthy control subjects (p=0.00001).
Table 2- Comparison of study variables between COVID-19 patients and healthy controls
Parameters |
Patients with COVID-19 (n=143) |
Healthy controls (n=143) |
P-value |
Mean age (years) |
50.04 |
52.89 |
>0.05 |
Gender |
Males (n=98)Females (n=45) |
Males (n=79)Females (n=64) |
>0.05 |
ANC/µl |
10561.85 ± 6865.41 |
3946.93 ± 1502.69 |
0.00001 |
As shown in table 2, the ANC of COVID-19 patients was significantly higher than that of healthy control subjects (p=0.00001).
Table 3- shows the frequency of morphological abnormalities in neutrophils of COVID-19 patients. The most common neutrophil abnormality was toxic granules (Figure 1).
Table 3- shows the frequency of morphological abnormalities in neutrophils of COVID-19 patients. The most common neutrophil abnormality was toxic granules (Figure 1).
| Morphology abnormalities | Number | Percent |
| Toxic granules | 70 | 48.9 |
| Pseudo-Pelger-Huet (Hypolobation) | 30 | 20.9 |
| Shift to left | 55 | 38.4 |
Figure 1-Microscopic images of neutrophil morphological changes. A) Hypolobated neutrophil; B and C) Toxic granules; D) Pseudo-Pelger-Huet anomaly and hypogranulation of neutrophil. All images were taken under 400X magnification.
DISCUSSION
Neutrophils are the predominant immune cells that protect the human body against bacterial, fungal, and viral infections (13). Activation of neutrophils leads to the release of neutrophil extracellular traps (NETs), which are a viscous network of nuclear chromatin, antimicrobial peptides, and enzymes that entrap microorganisms. Neutrophils produce NETs in response to inflammatory mediators and infectious pathogens, such as bacteria and fungi. During NETs formation, the nuclei of neutrophils are lost. The presence of NETs in the blood has also been reported during sepsis (14,15). The release of NETs disperses histones, DNA, and granule proteins, such as myeloperoxidase, neutrophil elastase, cathepsin G, and proteinase 3, which results in severe tissue destruction, setting up the auto-amplification loop of necrosis and inflammation. This plays an important role in vascular thromboinflammation, which causes cardiovascular disease in COVID-19 patients (15). The increased number of circulating neutrophils is an indicator of a worse outcome in COVID-19 (16, 17). Many studies have found a correlation between the severity of illness in the early stages of SARS-CoV-2 infection and elevated ANC and other inflammatory biomarkers (10, 17-21). The normal range of ANC is 2000-7000 cells/cumm (22). In the present study, the mean ANC (10600 cells/cumm) in our study was higher than that in similar studies (10, 23, 24).
Our findings indicate a probable correlation between COVID-19 and high ANC.
Lymphopenia in SARS-CoV-2 infection occurs due to the cytotoxic destruction of lymphocytes by cytokine storm and increased levels of IL-6, IL-8, lactic acid, and angiotensin-converting enzyme 2 on the surface of lymphocytes. This also contributes to the increased NLR ratio in COVID-19 and has a high prognostic value (18,21,25).
It has been reported that men and older individuals are at higher risk of contracting COVID-19 (16). The mean age of the patients in the present was 50.04 years, which is similar to the findings of some previous studies (16, 23).
In the present study, toxic granules (48.9%) were the most common morphological neutrophil abnormality, followed by hypolobation, hypogranulation, PHA anomaly (20.9%), and shift to left with the presence of immature myeloid series cells. These findings are consistent with the findings of Kaur et al. (26) and Bhalchandra et al. (27).
CONCLUSION
Based on the results of our study, high ANC along with morphological changes in neutrophils could be used as a surrogate marker of COVID-19 and its severity.
ACKNOWLEDGEMENTS
We are thankful to Mrs. Swati Raje for her comments on the statistical analysis of data.
DECLARATIONS
FUNDING
The authors received no financial support for the research, authorship, and/or publication of this article.
Ethics approvals and consent to participate
Written informed consent was taken from all subjects. Ethics approval was also obtained from the Institutional Ethics Committee (Approval code: no.IEC/MIMER/2022/784).
CONFLICT OF INTEREST
The authors declare that there is no conflict of interest regarding the publication of this article.
Neutrophils are the predominant immune cells that protect the human body against bacterial, fungal, and viral infections (13). Activation of neutrophils leads to the release of neutrophil extracellular traps (NETs), which are a viscous network of nuclear chromatin, antimicrobial peptides, and enzymes that entrap microorganisms. Neutrophils produce NETs in response to inflammatory mediators and infectious pathogens, such as bacteria and fungi. During NETs formation, the nuclei of neutrophils are lost. The presence of NETs in the blood has also been reported during sepsis (14,15). The release of NETs disperses histones, DNA, and granule proteins, such as myeloperoxidase, neutrophil elastase, cathepsin G, and proteinase 3, which results in severe tissue destruction, setting up the auto-amplification loop of necrosis and inflammation. This plays an important role in vascular thromboinflammation, which causes cardiovascular disease in COVID-19 patients (15). The increased number of circulating neutrophils is an indicator of a worse outcome in COVID-19 (16, 17). Many studies have found a correlation between the severity of illness in the early stages of SARS-CoV-2 infection and elevated ANC and other inflammatory biomarkers (10, 17-21). The normal range of ANC is 2000-7000 cells/cumm (22). In the present study, the mean ANC (10600 cells/cumm) in our study was higher than that in similar studies (10, 23, 24).
Our findings indicate a probable correlation between COVID-19 and high ANC.
Lymphopenia in SARS-CoV-2 infection occurs due to the cytotoxic destruction of lymphocytes by cytokine storm and increased levels of IL-6, IL-8, lactic acid, and angiotensin-converting enzyme 2 on the surface of lymphocytes. This also contributes to the increased NLR ratio in COVID-19 and has a high prognostic value (18,21,25).
It has been reported that men and older individuals are at higher risk of contracting COVID-19 (16). The mean age of the patients in the present was 50.04 years, which is similar to the findings of some previous studies (16, 23).
In the present study, toxic granules (48.9%) were the most common morphological neutrophil abnormality, followed by hypolobation, hypogranulation, PHA anomaly (20.9%), and shift to left with the presence of immature myeloid series cells. These findings are consistent with the findings of Kaur et al. (26) and Bhalchandra et al. (27).
CONCLUSION
Based on the results of our study, high ANC along with morphological changes in neutrophils could be used as a surrogate marker of COVID-19 and its severity.
ACKNOWLEDGEMENTS
We are thankful to Mrs. Swati Raje for her comments on the statistical analysis of data.
DECLARATIONS
FUNDING
The authors received no financial support for the research, authorship, and/or publication of this article.
Ethics approvals and consent to participate
Written informed consent was taken from all subjects. Ethics approval was also obtained from the Institutional Ethics Committee (Approval code: no.IEC/MIMER/2022/784).
CONFLICT OF INTEREST
The authors declare that there is no conflict of interest regarding the publication of this article.
Research Article: Original Paper |
Subject:
Laboratory hematology
Received: 2022/05/22 | Accepted: 2022/08/31 | Published: 2022/11/25 | ePublished: 2022/11/25
Received: 2022/05/22 | Accepted: 2022/08/31 | Published: 2022/11/25 | ePublished: 2022/11/25
References
1. Tay MZ, Poh CM, Rénia L, MacAry PA, Ng LFP. The trinity of COVID-19: immunity, inflammation and intervention. Nat Rev Immunol. 2020 ;20(6):363-374. [DOI:10.1038/s41577-020-0311-8] [PubMed] [Google Scholar]
2. Cavalcante-Silva LHA, Carvalho DCM, Lima ÉA, Galvão JGFM, da Silva JSF, Sales-Neto JM, et al. Neutrophils and COVID-19: The road so far. Int Immunopharmacol. 2021 ;90:107233. [View at Publisher] [DOI:10.1016/j.intimp.2020.107233.] [PubMed] [Google Scholar]
3. Andersen KG, Rambaut A, Lipkin WI, Holmes EC, Garry RF. The proximal origin of SARS-CoV-2. Nat Med. 2020 ;26(4):450-452. [DOI:10.1038/ s41591-020-0820-9.] [PubMed] [Google Scholar]
4. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020 15;395(10223):497-506. [View at Publisher] [DOI:10.1016/S0140-6736(20)30183-5] [PubMed] [Google Scholar]
5. Reusch N, De Domenico E, Bonaguro L, Schulte-Schrepping J, Baßler K, Schultze JL,et al. Neutrophils in COVID-19. Front Immunol. 2021 25;12:652470. [DOI:10.3389/fimmu.2021.652470] [PubMed] [Google Scholar]
6. Soehnlein O, Steffens S, Hidalgo A, Weber C. Neutrophils as protagonists and targets in chronic inflammation. Nat Rev Immunol. 2017 ;17(4):248-261. [DOI:10.1038/nri.2017.10] [PubMed] [Google Scholar]
7. Tomar B, Anders HJ, Desai J, Mulay SR. Neutrophils and Neutrophil Extracellular Traps Drive Necroinflammation in COVID-19. Cells. 2020 2;9(6):1383. [DOI:10.3390/cells9061383] [PubMed] [Google Scholar]
8. Galani IE, Andreakos E. Neutrophils in viral infections: Current concepts and caveats. J Leukoc Biol. 2015 ;98(4):557-64. [View at Publisher] [DOI:10.1189/jlb.4VMR1114-555R] [PubMed] [Google Scholar]
9. Naumenko V, Turk M, Jenne CN, Kim SJ. Neutrophils in viral infection. Cell Tissue Res. 2018 ;371(3):505-516. [View at Publisher] [DOI:10.1007/s00441-017-2763-0] [PubMed] [Google Scholar]
10. Wang J, Li Q, Yin Y, Zhang Y, Cao Y, Lin X, et al . Excessive Neutrophils and Neutrophil Extracellular Traps in COVID-19. Front Immunol. 2020 18;11:2063. [DOI:10.3389/fimmu.2020.02063] [PubMed] [Google Scholar]
11. Singh K, Mittal S, Gollapudi S, Butzmann A, Kumar J, Ohgami RS. A meta-analysis of SARS-CoV-2 patients identifies the combinatorial significance of D-dimer, C-reactive protein, lymphocyte, and neutrophil values as a predictor of disease severity. Int J Lab Hematol. 2021 ;43(2):324-328. [View at Publisher] [DOI:10.1111/ijlh.13354] [PubMed] [Google Scholar]
12. Guan J, Wei X, Qin S, Liu X, Jiang Y, Chen Y, et al . Continuous tracking of COVID-19 patients' immune status. Int Immunopharmacol. 2020 ;89(Pt A):107034. [View at Publisher] [DOI:10.1016/j.intimp.2020.107034] [PubMed] [Google Scholar]
13. Radermecker C, Detrembleur N, Guiot J, Cavalier E, Henket M, d'Emal C, et al. Neutrophil extracellular traps infiltrate the lung airway, interstitial, and vascular compartments in severe COVID-19. J Exp Med. 2020 7;217(12):e20201012. [View at Publisher] [DOI:10.1084/jem.20201012] [PubMed] [Google Scholar]
14. Kumar V, Abbas AK, Fausto N, Aster JC. Robbins and Cotran pathologic basis of disease, professional edition e-book. Elsevier health sciences; 2014 Aug 27. [Google Scholar]
15. Leppkes M, Knopf J, Naschberger E, Lindemann A, Singh J, Herrmann I, et al. Vascular occlusion by neutrophil extracellular traps in COVID-19. EBioMedicine. 2020 ;58:102925. [View at Publisher] [DOI:10.1016/j.ebiom.2020.102925] [PubMed] [Google Scholar]
16. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020 15;395(10223):497-506. [View at Publisher] [DOI:10.1016/S0140-6736(20)30183-5] [PubMed] [Google Scholar]
17. Zeng Z, Yu H, Chen H, Qi W, Chen L, Chen G,et al. Longitudinal changes of inflammatory parameters and their correlation with disease severity and outcomes in patients with COVID-19 from Wuhan, China. Crit Care. 2020 27;24(1):525. [View at Publisher] [DOI:10.1186/s13054-020-03255-0] [PubMed] [Google Scholar]
18. Fu J, Kong J, Wang W, Wu M, Yao L, Wang Z,et al. The clinical implication of dynamic neutrophil to lymphocyte ratio and D-dimer in COVID-19: A retrospective study in Suzhou China. Thromb Res. 2020 ;192:3-8. [View at Publisher] [DOI:10.1016/j.thromres.2020.05.006] [PubMed] [Google Scholar]
19. Webb BJ, Peltan ID, Jensen P, Hoda D, Hunter B, Silver A, et al. Clinical criteria for COVID-19-associated hyperinflammatory syndrome: a cohort study. Lancet Rheumatol. 2020 Dec;2(12):e754-e763. [View at Publisher] [DOI:10.1016/S2665-9913(20)30343-X] [PubMed] [Google Scholar]
20. 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):389-399. [DOI:10.1080/10408363.2020.1770685] [PubMed] [Google Scholar]
21. Tan L, Wang Q, Zhang D, Ding J, Huang Q, Tang YQ,et al. Lymphopenia predicts disease severity of COVID-19: a descriptive and predictive study. Signal Transduct Target Ther. 2020 27;5(1):33. [DOI:10.1038/s41392-020-0159-1] [PubMed] [Google Scholar]
22. Bain BJ, Bates I, Laffan MA. Dacie and lewis practical haematology e-book. Elsevier Health Sciences; 2016 Aug 11. [Google Scholar]
23. Gee S, Taylor D. The effect of COVID-19 on absolute neutrophil counts in patients taking clozapine. Ther Adv Psychopharmacol. 2020 16;10:2045125320940935. [DOI:10.1177/2045125320940935] [PubMed] [Google Scholar]
24. Chao WC, Wu CL, Huang JA, Chai JW, Teng CL, Lee WL,et al. Association between Early Absolute Neutrophil Count and Level of D-Dimer among Patients with COVID-19 Infection in Central Taiwan. J Clin Med. 2021 30;10(17):3891. [DOI:10.3390/jcm10173891] [PubMed] [Google Scholar]
25. Jain R, Gopal A, Pathak BK, Mohakuda SS, Tilak T, Singh AR. Neutrophil-to-Lymphocyte Ratio and Platelet-to-Lymphocyte Ratio and Their Role as Predictors of Disease Severity of Coronavirus Disease 2019 (COVID-19). J Lab Physicians. 2021 ;13(1):58-63. [DOI:10.1055/s-0041-1723057] [PubMed] [Google Scholar]
26. Kaur G, Sandeep F, Olayinka O, Gupta G. Morphologic Changes in Circulating Blood Cells of COVID-19 Patients. Cureus. 2021 18;13(2):e13416. [DOI:10.7759/cureus.13416] [PubMed] [Google Scholar]
27. Bhalchandra AR, Siddharth R, Mallikarjun G, Prabhakar M, Nath A. Morphological Changes in Peripheral Blood in COVID-19 Infection. Int Arch BioMed Clin Res [Internet]. 2021.31 [cited 2022Sep.30];7(4):LM1-LM6. [Google Scholar]
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
Enamad
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.