The role of haematological parameters in patients with COVID-19 and influenza virus infection

医学 血小板 2019年冠状病毒病(COVID-19) 淋巴细胞 免疫学 内科学 中性粒细胞与淋巴细胞比率 胃肠病学 严重急性呼吸综合征冠状病毒2型(SARS-CoV-2) 疾病严重程度 疾病 传染病(医学专业)
作者
Sümeyye Kazancıoğlu,Aliye Baştuğ,Bahadır Orkun Özbay,Nizamettin Kemirtlek,Hürrem Bodur
出处
期刊:Epidemiology and Infection [Cambridge University Press]
卷期号:148 被引量:47
标识
DOI:10.1017/s095026882000271x
摘要

Abstract SARS-CoV-2, the causative agent of coronavirus disease 19 (COVID-19), was identified in Wuhan, China. Since then, the novel coronavirus started to be compared to influenza. The haematological parameters and inflammatory indexes are associated with severe illness in COVID-19 patients. In this study, the laboratory data of 120 COVID-19 patients, 100 influenza patients and 61 healthy controls were evaluated. Lower lymphocytes, eosinophils, basophils, platelets and higher delta neutrophil index (DNI), neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) were found in COVID-19 and influenza groups compared to healthy controls. The eosinophils, lymphocytes and PLR made the highest contribution to differentiate COVID-19 patients from healthy controls (area under the curves (AUCs): 0.819, 0.817 and 0.716, respectively; P -value is <0.0001 for all). The NLR, the optimal cut-off value was 3.58, which resulted in a sensitivity of 30.8 and a specificity of 100 (AUC: 0.677, P < 0.0001). Higher leucocytes, neutrophils, DNI, NLR, PLR and lower lymphocytes, red blood cells, haemoglobin, haematocrit levels were found in severe patients at the end of treatment. Nonsevere patients showed an upward trend for lymphocytes, eosinophils and platelets, and a downward trend for neutrophils, DNI, NLR and PLR. However, there was an increasing trend for eosinophils, platelets and PLR in severe patients. In conclusion, NLR and PLR can be used as biomarkers to distinguish COVID-19 patients from healthy people and to predict the severity of COVID-19. The increasing value of PLR during follow-up may be more useful compared to NLR to predict the disease severity.
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