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DOI: 10.1055/s-0041-1723057
Neutrophil-to-Lymphocyte Ratio and Platelet-to-Lymphocyte Ratio and Their Role as Predictors of Disease Severity of Coronavirus Disease 2019 (COVID-19)
Abstract
Context Due to the wide spectrum of clinical illness in coronavirus disease 2019 (COVID-19) patients, it is important to stratify patients into severe and nonsevere categories. Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have been evaluated rapidly by a few studies worldwide for its association with severe disease, but practically none have been conducted in the Indian population. This study was undertaken to examine the role of NLR and PLR in predicting severe disease in Indian patients.
Objectives The objective was to study the association of NLR and PLR observed at the time of admission with maximum disease severity during hospitalization and to study their role in predicting disease severity.
Material and Methods A total of 229 COVID-19 patients were admitted at the center during the study period. After applying inclusion and exclusion criteria, 191 patients were included in the study. The demographic, clinical, and laboratory (complete blood count, NLR, and PLR) data of all patients were obtained at the time of admission. Maximum disease severity of all patients was assessed during hospitalization.
Statistical Analysis Chi-square and Mann–Whitney U tests were used to assess statistical significance. Receiver operating characteristic curve (ROC) was plotted for NLR and PLR to estimate the cutoff values and sensitivity and specificity using Youden’s index for predicting severe disease. Logistic regression analysis was used to estimate the odds ratios (OR) and 95% confidence intervals.
Results Mean NLR and PLR were significantly higher in severe patients (NLR = 7.41; PLR = 204) compared with nonsevere patients (NLR = 3.30; PLR = 121). ROC analysis showed that NLR, in comparison to PLR, had a higher area under the curve (AUC) of 0.779, with a larger OR of 1.237 and cutoff of 4.1, and showed 69% sensitivity and 78% specificity in predicting severe disease. Cut off for PLR was 115.3, which showed 79% sensitivity and 62% specificity in predicting severe disease.
Conclusion NLR and PLR, both showing acceptable AUCs, can be used as screening tools to predict disease severity. However, NLR was a better predictor of disease severity.
Publikationsverlauf
Artikel online veröffentlicht:
22. Februar 2021
© 2021. The Indian Association of Laboratory Physicians. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).
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References
-
1 World Health Organization. Pneumonia of cause – China. Available at: http://www.who.int/csr/don/05-january-2020-pneumonia-of-unkown-cause-china/en/. Accessed July 7, 2020
-
2 Xinhuanet. New-type coronavirus causes pneumonia in Wuhan. Available at: http://www.xinhuanet.com/english/2020-01/09/c_138690570.htm. Accessed July 7, 2020
- 3 Zhu N, Zhang D, Wang W. et al; China Novel Coronavirus Investigating and Research Team. A novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med 2020; 382 (08) 727-733
-
4 Worldometer. Coronavirus Cases. Available at: https://www.worldometers.info/coronavirus/country/india/. Accessed August 31, 2020
- 5 Słomka A, Kowalewski M, Żekanowska E. Coronavirus disease 2019 (COVID-19): a short review on hematological manifestations. Pathogens 2020; 9 (06) 493
- 6 Terpos E, Ntanasis-Stathopoulos I, Elalamy I. et al. Hematological findings and complications of COVID-19. Am J Hematol 2020; 95 (07) 834-847
- 7 Li Q, Cao Y, Chen L. et al. Hematological features of persons with COVID-19. Leukemia 2020; 34 (08) 2163-2172
- 8 Henry BM, de MHS Oliveira, Benoit S, Plebani M, Lippi G. Hematologic, biochemical and immune biomarker abnormalities associated with severe illness and mortality in coronavirus disease 2019 (COVID-19): a meta-analysis. Clin Chem Lab Med 2020; 58 (07) 1021-1028
- 9 Yang AP, Liu JP, Tao WQ, Li HM. The diagnostic and predictive role of NLR, d-NLR and PLR in COVID-19 patients. Int Immunopharmacol 2020; 84: 106504
- 10 Qu R, Ling Y, Zhang YH. et al. Platelet-to-lymphocyte ratio is associated with prognosis in patients with coronavirus disease-19. J Med Virol 2020; (e-pub ahead of print) DOI: 10.1002/jmv.25767.
- 11 Shang W, Dong J, Ren Y. et al. The value of clinical parameters in predicting the severity of COVID-19. J Med Virol 2020; (e-pub ahead of print) DOI: 10.1002/jmv.26031.
- 12 Chan AS, Rout A. Use of neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios in COVID-19. J Clin Med Res 2020; 12 (07) 448-453
- 13 Liu Y, Du X, Chen J. et al. Neutrophil-to-lymphocyte ratio as an independent risk factor for mortality in hospitalized patients with COVID-19. J Infect 2020; 81 (01) e6-e12
- 14 Tan L, Wang Q, Zhang D. et al. Lymphopenia predicts disease severity of COVID-19: a descriptive and predictive study. Signal Transduct Target Ther 2020; 5 (01) 33
- 15 Xu P, Zhou Q, Xu J. Mechanism of thrombocytopenia in COVID-19 patients. Ann Hematol 2020; 99 (06) 1205-1208
-
16 Clinical management protocol: COVID-19, Ministry of Health and Family Welfare (MOHFW), Government of India (GOI) dated 03/07/2020; Version 5
- 17 Bain B, Bates I, Laffan M. Dacie and Lewis Practical Haematology.. China: Elsevier; 2017