Comparative analysis of neutrophil to lymphocyte ratio and derived neutrophil to lymphocyte ratio with respect to outcomes of in-hospital coronavirus disease 2019 patients: A retrospective study - Asghar, Muhammad Sohaib; Akram, Mohammed; Yasmin, Farah; Najeeb, Hala; Naeem, Unaiza; Gaddam, Mrunanjali; Jafri, Muhammad Saad; Tahir, Muhammad Junaid; Yasin, Iqra; Mahmood, Hamid; Mehmood, Qasim; Marzo, Roy Rillera (Frontiers in Medicine, 2022)
Introduction & objectives: In patients with coronavirus disease 2019 (COVID-19), several abnormal hematological biomarkers have been reported. The current study aimed to find out the association of neutrophil to lymphocyte ratio (NLR) and derived NLR (dNLR) with COVID-19. The objective was to compare the accuracy of both of these markers in predicting the severity of the disease. Materials & methods: The study was conducted in a single-center having COVID-19 patients with considerable hospital stay. NLR is easily calculated by dividing the absolute neutrophil count (ANC) with the absolute lymphocyte count (ALC) ANC/ALC, while dNLR is calculated by Absolute neutrophil count divided by total leukocyte count minus absolute neutrophil count ANC/(WBC−ANC). Medians and interquartile ranges (IQR) were represented by box plots. Multivariable logistic regression was performed obtaining odds ratio (OR), 95% confidence intervals (95% CI), and further adjusted to discover the independent predictors and risk factors associated with elevated NLR and dNLR. Results: A total of 1000 patients with COVID-19 were included. Baseline NLR and dNLR were 5.00 (2.91–10.46), and 4.00 (2.33–6.14), respectively. A cut-off value of 4.23 for NLR and 2.63 for dNLR were set by receiver operating characteristic (ROC) analysis. Significant associations of NLR were obtained by binary logistic regression for dependent outcome variables as ICU stay (p<0.001), death (p<0.001), and invasive ventilation (p<0.001) while that of dNLR with ICU stay (p=0.002), death (p<0.001), and invasive ventilation (p=0.002) on multivariate analysis when adjusted for age, gender and wave of pandemics. Moreover, the indices were found correlating with other inflammatory markers such as C-reactive protein, D-dimer, and procalcitonin. Conclusion: Both markers are equally reliable and sensitive to predict in-hospital outcomes of COVID-19 patients. Early detection and predictory analysis of these markers can allow physicians for risk assessment and prompt management of these patients.