Assessing the Predictive Value of Haematological Parameters (NLR, LMR, PLR) for COVID-19 Disease Severity as quantified by CT Severity Scores: A Prospective Cohort Study

Abstract

Introduction: In the relentless global battle against the Coronavirus Disease-2019 (COVID-19) pandemic, accurate prediction of disease severity remains a critical challenge, with profound implications for patient outcomes and healthcare resource allocation. As the virus continues to evolve and pose new threats, the need for reliable prognostic indicators becomes increasingly urgent. Effective identification of patients at highrisk of developing severe illness not only facilitates timely intervention and personalised treatment strategies but also optimises healthcare resource utilisation. In this context, the exploration of novel biomarkers and predictive models holds immense promise for enhancing ones understanding of disease progression and improving clinical decision-making. Aim: To study the association between haematological parameters, including Neutrophil-to-Lymphocyte Ratio (NLR), Lymphocyte-to-Monocyte Ratio (LMR), and Platelet-toLymphocyte Ratio (PLR), with Computed Tomography Scan Severity Score (CTSS) in COVID-19 patients. Materials and Methods: A prospective cohort study was conducted from March 2021 to July 2022 at Government General Hospital (GGH) Nizamabad, Telangana, India. The study encompassed all three COVID-19 waves, included a sample size of 159 Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) positive patients, excluding pregnant women and children under 10 years. Upon admission, CTSS and ratios of NLR, LMR, and PLR were recorded in an MS Excel sheet before any medical intervention and then analysed using Statistical Package for Social Sciences (SPSS) software 22.0. Results: The study comprised 159 patients with a mean age of 50.86±13.89 years (ranging from 16 to 85), predominantly male 90 (56.61%). The highest infection rate 85 (53.45%) was in the 41-60 years age group. The NLR was significantly elevated from a mean value of 4.58 to 11.24 (r value=0.78, p-value=<0.001), and LMR notably reduced from 8.27 to 3.80 (r value=0.67, p-value=0.003) in correlation with the severity as indicated by CTSS. Although PLR values were higher in severe cases, increasing from 173.07 in mild cases to 272.29 in severe cases, there was no significant correlation with CTSS (r-value=-0.78, p-value=0.177). Conclusion: CTSS emerges as a valuable radiological biomarker for predicting COVID-19 severity. However, due to its cost and limited availability in grassroots-level hospitals, there is a need for alternative severity prediction models. Present study proposes a predictive model using NLR and LMR biomarkers as alternatives to CTSS for assessing COVID-19 severity.