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?:abstract
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BACKGROUND: The emergence and rapid spread of the deadly novel coronavirus disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a swiftly evolving public health crisis worldwide SARS-CoV-2 infection is characterized by the development and progression of inflammatory responses Hematological parameters, such as white blood cells (WBCs) and their subpopulations, red cell distribution width, platelet count, mean platelet volume, plateletcrit, and derived markers such as neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio, are established biomarkers of inflammatory responses We aimed to investigate associations between hematological parameters and disease severity in patients with SARS-CoV-2 infection METHODS: We retrospectively analyzed data from 68 patients with confirmed SARS-CoV-2 infection Twenty-two patients had mild illness, and 46 had moderate or severe illness at the time of admission Univariate and multivariate regression analyses were used to identify correlates of disease severity The areas under receiver operating characteristic curves were calculated to estimate and compare the predictive values of different diagnostic markers RESULTS: Mean lymphocyte and monocyte counts were lower while WBC counts, neutrophil counts, NLR, and PLR were higher in patients with severe disease compared with those with mild disease (all P < 01) Univariate analysis revealed that older age, high WBC counts, high neutrophil counts, high NLR, high PLR, low monocyte counts, and low lymphocyte counts were independent correlates of severe illness Multivariate analysis identified high NLR as the only independent correlate of severe illness Receiver operating characteristic curve analysis showed that NLR had the highest area under curve of all hematological parameters CONCLUSION: Among hematological parameters, the NLR showed superior prediction of disease severity in patients with SARS-CoV-2 infection Thus, the NLR could be a valuable parameter to complement conventional measures for identification of patients at high risk for severe disease
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