Evaluation of NLR, d-NLR, and PLR in terms of disease severity in COVID-19 patients

Öz

Some circulating biomarkers that may represent inflammation and immune status may be potential predictors for the prognosis of COVID-19 patients. Peripheral white blood cell (WBC) count, neutrophil-to-lymphocyte ratio (NLR), derived NLR ratio [d-NLR, neutrophil count/(WBC count - neutrophil count)], and platelet-lymphocyte ratio (PLR) are useful biomarkers for the prognosis of patients with viral pneumonia. In this study, we aimed to evaluate the severity of the disease in COVID-19 patients using NLR, d-NLR, and PLR biomarkers. Patients who were followed up and treated with the diagnosis of COVID-19 for one year starting from April 2020 were included in the study. Patients with positive SARS-COV-2 PCR test or negative PCR results but with typical lung CT findings such as peripheral, bilateral, or multifocal round ground-glass opacity were included in the study if the clinical picture could not be explained by any other reason. According to the guidance of the World Health Organization (WHO) and the Ministry of Health of the Republic of Turkey, COVID-19 diagnosis and treatment guidelines, patients were grouped as severe and non-severe COVID-19. Of the 395 patients included, median age was 66.5% and 52.7% of the patients were female. Advanced age (<0.001), high d-NLR (0.027), and CRP (<0.001) levels were significantly associated with COVID-19 disease severity. Comorbidity, diabetes, heart disease, and COPD rates were statistically significantly higher in COVID-19 patients with severe disease (<0.001, 0.022, 0.004, and 0.027, respectively). NLR, d-NLR, and PLR values were higher in severe COVID-19 patients than in non-serious patients. Although our findings support the use of d-NLR levels in clinical practice, further studies should be developed to obtain a definitive consensus threshold.

Anahtar Kelimeler

• COVID-19
• SARS-COV-2
• NLR
• d-NLR ve PLR

COVID-19 HASTALARINDA NLR, d-NLR VE PLR'NİN HASTALIK CİDDİYETİ AÇISINDAN DEĞERLENDİRİLMESİ*

Öz

İnflamasyonu ve bağışıklık durumunu temsil edebilen dolaşımdaki bazı biyobelirteçler, COVID-19 hastalarının prognozu için potansiyel öngörücü olabilmektedir. Periferik beyaz kan hücresi (WBC) sayısı, nötrofil-lenfosit oranı (NLR), türetilmiş NLR oranı [d-NLR, nötrofil sayısı/ (WBC sayısı- nötrofil sayısı)] ve trombosit-lenfosit oranı (PLR) viral pnömonili hastaların prognozu için yararlı prediktör olarak sistematik inflamatuar cevabın göstergeleridir. Bu çalışmada COVID-19 hastalarında NLR, d-NLR ve PLR biyobelirteçleri kullanılarak hastalık ciddiyetinin değerlendirilmesi amaçlanmıştır. COVID-19 tanısıyla 2020 yılı Nisan ayından itibaren bir yıllık süreçte takip ve tedavileri yapılan hastalar çalışmaya alınmıştır. SARS-COV-2 PCR testi pozitif olan veya PCR sonuçları negatif olan ancak periferik, bilateral veya multifokal yuvarlak buzlu cam opasitesi gibi tipik Akciğer BT bulguları olan hastalar, klinik tablo başka bir nedenle açıklanamıyorsa çalışmaya dahil edilmiştir. Dünya Sağlık Örgütü (DSÖ) ve T.C. Sağlık Bakanlığı COVID-19 tanı ve tedavi kılavuzları rehberliğine göre hastalar ciddi ve ciddi olmayan COVID-19 olarak gruplanmıştır. Çalışmaya alınan 395 hastanın ortanca yaşı 66.5 idi ve %52.7’si kadındı. İleri yaş (<.001), yüksek d-NLR (0.027) ve CRP (<0.001) düzeyleri COVID-19 hastalık ciddiyeti ile önemli ölçüde ilişkiliydi. Komorbidite, diyabet, kalp hastalığı ve KOAH ciddi hastalık tablosu olan COVID-19 hastalarında istatistiksel olarak anlamlı derecede yüksek oranda izlendi (Sırasıyla <0.001, 0.022, 0.004 ve 0.027). Ciddi COVID-19 hastalarında, ciddi olmayan hasta grubuna göre NLR, d-NLR ve PLR değerleri daha yüksek seyretmiştir. Bulgularımız klinik pratikte d-NLR düzeylerinin kullanımını desteklemekle birlikte, kesin bir konsensüs eşik değeri elde etmek için daha ileri çalışmalar geliştirilmelidir.

Anahtar Kelimeler

• COVID-19
• SARS-COV-2
• NLR
• d-NLR ve PLR

Kaynakça

1. 1. Acar E, Demir A, Yıldırım B, Kaya MG, Gökçek K. The role of hemogram parameters and C-reactive protein in predicting mortality in COVID-19 infection. Int J Clin Pract. 2021;75(7):e14256. https://doi.org/10.1111/ijcp.14256
2. 2. 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. https://doi.org/10.1002/hsr2.663
3. 3. Ben Jemaa A, Salhi N, Ben Othmen M, Ben Ali H, Guissouma J, Ghadhoune H, Oueslati R, Dhaouadi H. Evaluation of individual and combined NLR, LMR and CLR ratio for prognosis disease severity and outcomes in patients with COVID-19. Int Immunopharmacol. 2022;109:108781. https://doi.org/10.1016/j.intimp.2022.108781
4. 4. Citu C, Gorun F, Motoc A, et al. The predictive role of NLR, d-NLR, MLR, and SIRI in COVID-19 mortality. Diagnostics (Basel). 2022;12(1):122. https://doi.org/10.3390/diagnostics12010122.
5. 5. Damar Çakırca T, Torun A, Çakırca G, Portakal RD. Role of NLR, PLR, ELR and CLR in differentiating COVID-19 patients with and without pneumonia. Int J Clin Pract. 2021;75(11):e14781. https://doi.org/10.1111/ijcp.14781
6. 6. Feng X, Li S, Sun Q, Zhu J, Chen B, Xiong M, Cao G. Immune-inflammatory parameters in COVID-19 cases: a systematic review and meta-analysis. Front Med (Lausanne). 2020;7:301. https://doi.org/10.3389/fmed.2020.00301
7. 7. Gibson PH, Croal BL, Cuthbertson BH, et al. Preoperative neutrophil-lymphocyte ratio and outcome from coronary artery bypass grafting. Am Heart J. 2007;154(5): 995-1002. https://doi.org/10.1016/j.ahj.2007.06.043
8. 8. Guthrie GJ, Charles KA, Roxburgh CS, Horgan PG, McMillan DC, Clarke SJ. The systemic inflammation-based neutrophil-lymphocyte ratio: experience in patients with cancer. Crit Rev Oncol Hematol. 2013;88(1):218-30. https://doi.org/10.1016/j.critrevonc.2013.03.010

9. 9. Han Q, Wen X, Wang L, et al. Role of hematological parameters in the diagnosis of influenza virus infection in patients with respiratory tract infection symptoms. J Clin Lab Anal. 2020;34(5):e23191. https://doi.org/10.1002/jcla.23191
10. 10. Lagunas-Rangel FA. Neutrophil-to-lymphocyte ratio and lymphocyte-to-C-reactive protein ratio in patients with severe coronavirus disease 2019 (COVID-19): A meta-analysis. J Med Virol. 2020;92(10):1733-4. https://doi.org/10.1002/jmv.25819
11. 11. Liu Y, Du X, Chen J, Jin Y, Peng L, Wang HHX, Luo M, Chen L, Zhao Y. Neutrophil-to-lymphocyte ratio as an independent risk factor for mortality in hospitalized patients with COVID-19. J Infect. 2020;81(1):e6-12. https://doi.org/10.1016/j.jinf.2020.04.002
12. 12. Olivieri F, Sabbatinelli J, Bonfigli AR, et al. Routine laboratory parameters, including complete blood count, predict COVID-19 in-hospital mortality in geriatric patients. Mech Ageing Dev. 2022;204(SI):111674. https://doi.org/10.1016/j.mad.2022.111674
13. 13. Polat C. Covid-19 Pandemisi: Genel Bir Bakış. ANKEM Derg. 2020;34(1):25-31. https://doi.org/10.5222/ankem.2020.025
14. 14. Prasetya IB, Cucunawangsih, Lorens JO, Sungono V, El-Khobar KE, Wijaya RS. Prognostic value of inflammatory markers in patients with COVID-19 in Indonesia. Clin Epidemiol Glob Health. 2021;11:100803. https://doi.org/10.1016/j.cegh.2021.100803
15. 15. Russell CD, Parajuli A, Gale HJ, et al. The utility of peripheral blood leucocyte ratios as biomarkers in infectious diseases: A systematic review and meta-analysis. J Infect. 2019;78(5):339-48. https://doi.org/10.1016/j.jinf.2019.02.006
16. 16. Sarkar S, Khanna P & Singh AK. The impact of neutrophil-lymphocyte count ratio in COVID-19: A systematic review and meta-analysis. J Intensive Care Med. 2021;37(7):857-9. https://doi.org/10.1177/08850666211045626
17. 17. Simadibrata DM, Calvin J, Wijaya AD, Ibrahim NAA. Neutrophil-to-lymphocyte ratio on admission to predict the severity and mortality of COVID-19 patients: A meta-analysis. Am J Emerg Med. 2021;42:60-9. https://doi.org/10.1016/j.ajem.2021.01.006
18. 18. 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. https://doi.org/10.1016/j.intimp.2020.106504
19. 19. Zheng Y, Xu H, Yang M, et al. Epidemiological characteristics and clinical features of 32 critical and 67 noncritical cases of COVID-19 in Chengdu. J Clin Virol. 2020;127:104366. https://doi.org/10.1016/j.jcv.2020.104366