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1- Department of Pathology, MES Medical College, Perinthalmanna, Malappuram District, Kerala state, India , aneeshaea@gmail.com
2- Department of Pathology, MES Medical College, Perinthalmanna, Malappuram District, Kerala state, India
3- Department of Pathology, MES Medical College, Perinthalmanna, Malappuram District, , Kerala state, India
Abstract:   (420 Views)
Background and Objectives: Covid-19 is a global pandemic, caused by Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2). So far different clinical and hematological findings that can predict disease severity have been identified. This study explores the role of 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: After obtaining Ethics committee clearance, patients with laboratory confirmed Covid-19 infection admitted during their first two weeks of illness were included in this prospective study. NLR, PLR and NPR were derived from the CBC reports. These ratios were compared in each clinical category groups to assess the severity.
Results: The total number of cases was 160. The mean age at diagnosis was 56 years. Proportion of males were slightly higher (54.4%) than that of females (45.6%). The proportion of Category C patients (66.9%) were more than Category B (25%) and Category A (8.1%) patients. It was found that the NLR, PLR and NPR ratios has statistically significant association with severe Covid-19 infection and hence these can be used to differentiate between Category C from Category A or B. NLR is the better parameter in predicting the severity of Covid-19 disease than PLR and NPR.
Conclusions: NLR, PLR and NPR ratios can be used as predictive markers of disease severity in Covid-19 infection. Among these ratios, NLR has the highest predictive value for disease deterioration.

 
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Research Article: Original Paper | Subject: Laboratory hematology
Received: 2023/05/9 | Accepted: 2023/10/9

References
1. Sriram K, Insel PA. Inflammation and thrombosis in COVID-19 pathophysiology: proteinase-activated and purinergic receptors as drivers and candidate therapeutic targets. Physiol Rev. 2021;101(2):545-67. [View at Publisher] [DOI] [PMID] [Google Scholar]
2. Anjorin AA. The coronavirus disease 2019 (COVID-19) pandemic: A review and an update on cases in Africa. Asian Pacific Journal of Tropical Medicine. 2020;13(5):199-203. [View at Publisher] [DOI] [Google Scholar]
3. Becker RC. COVID-19 update: Covid-19-associated coagulopathy. J Thromb Thrombolysis. 2020;50(1):54-67. [View at Publisher] [DOI] [PMID] [Google Scholar]
4. Ruan Q, Yang K, Wang W, Jiang L, Song J. Clinical predictors of mortality due to COVID- 19 based on an analysis of data of 150 patients from Wuhan, China. Intensive Care Med. 2020;46(5):846-8. [View at Publisher] [DOI] [PMID] [Google Scholar]
5. Guan W-J, Liang W-H, Zhao Y, Liang H-R, Chen Z-SH, Li Y-M, et al. Comorbidity and its impact on 1590 patients with COVID-19 in China: a nationwide analysis. Eur Respir J. 2020;55(5):2000547. [View at Publisher] [DOI] [PMID] [Google Scholar]
6. Goyal P, Choi JJ, Pinheiro LC, Schenck EJ, Chen R, Jabri A, et al. Clinical characteristics of Covid-19 in New York City. N Engl J Med. 2020;382(24):2372-4. [View at Publisher] [DOI] [PMID] [Google Scholar]
7. Li Y, Hu Y, Yu J, Ma T. Retrospective analysis of laboratory testing in 54 patients with severe-or critical-type 2019 novel coronavirus pneumonia. Lab Invest. 2020;100(6):794-800. [View at Publisher] [DOI] [PMID] [Google Scholar]
8. Liu J, Liu Y, Xiang P, Pu L, Xiong H, Li C, et al. Neutrophil-to-lymphocyte ratio predicts critical illness patients with 2019 coronavirus disease in the early stage. J Transl Med. 2020;18(1):206. [View at Publisher] [DOI] [PMID] [Google Scholar]
9. Nalbant A, Kaya T, Varim C, Yaylaci S, Tamer A, Cinemre H. Can the neutrophil/lymphocyte ratio (NLR) have a role in the diagnosis of coronavirus 2019 disease (COVID-19). Rev Assoc Med Bras . 2020;66(6):746-51. [View at Publisher] [DOI] [PMID] [Google Scholar]
10. Shi S, Liu X, Xiao J, Wang H, Chen L, Li J, et al. Prediction of adverse clinical outcomes in patients with coronavirus disease 2019. J Clin Lab Anal. 2021;35(1):e23598. [View at Publisher] [DOI] [PMID] [Google Scholar]
11. Samprathi M, Jayashree M. Biomarkers in COVID-19: an up-to-date review. Front Pediatr. 2021;8:607647. [View at Publisher] [DOI] [PMID] [Google Scholar]
12. Nazarullah A, Liang C, Villarreal A, Higgins RA, Mais DD. Peripheral blood examination findings in SARS-CoV-2 infection. Am J Clin Pathol. 2020;154(3):319-29. [View at Publisher] [DOI] [PMID] [Google Scholar]
13. Dubey DB, Mishra S, Reddy HD, Rizvi A, Ali W. Hematological and serum biochemistry parameters as a prognostic indicator of severally ill versus mild Covid-19 patients: A study from tertiary hospital in North India. Clin Epidemiol Glob Health. 2021;12:100806. [View at Publisher] [DOI] [PMID] [Google Scholar]
14. Yang A-P, Liu J-P, Tao W-Q, Li H-M. The diagnostic and predictive role of NLR, d-NLR and PLR in COVID-19 patients. Int Immunopharmacol. 2020;84:106504. [View at Publisher] [DOI] [PMID] [Google Scholar]
15. Asaduzzaman MD, Romel Bhuia M, Nazmul Alam Z, Zabed Jillul Bari M, Ferdousi T. Significance of hemogram‐derived ratios for predicting in‐hospital mortality in COVID‐19: A multicenter study. Health Sci Rep. 2022;5(4):e663. [View at Publisher] [DOI] [PMID] [Google Scholar]
16. Chan AS, Rout A. Use of neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios in COVID-19. J Clin Med Res. 2020;12(7):448-53. [View at Publisher] [DOI] [PMID] [Google Scholar]
17. Akan OY, Bilgir O. Effects of neutrophil/monocyte, neutrophil/lymphocyte, neutrophil/platelet ratios and c-reactive protein levels on the mortality and intensive care need of the patients diagnosed with Covid-19. EJMI. 2021;5(1):21-5. [View at Publisher] [DOI] [Google Scholar]

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