HRCT severity score as a predictive biomarker in severity assessment of COVID-19 patients

Background/Aim: In 2020, the World Health Organization declared the Coronavirus disease of 2019 (COVID-19) a pandemic due to its widespread nature. The severity of COVID-19 infections leading to patient deaths is influenced by various factors. Therefore, it is crucial to identify and address these contributing causes for effective treatment of COVID-19. Methods: This study was conducted between 23 January 2021 and 19 June 2021 at a hospital with 100 beds in Western Nepal. Patient demographic data and High-resolution computed tomography severity scores were recorded. Microsoft Excel and Statistical Package for the Social Sciences were used for statistical data analysis. Binomial regression and Chi-square tests were applied, setting the significance level at P<0.05 with a confidence interval of 95%. Results: The study found a significant association between computed tomography (CT) severity, gender, and age with the treatment outcome among COVID-19-infected patients admitted to the hospital. Patients with a CT severity score between 16 and 25 had an eightfold higher mortality rate (OR: -8.802; 95% CI: 3.506–18.491). Conclusion: The severity and mortality of COVID-19 infections are influenced by factors such as age, gender, and biomarkers indicated by CT severity scores. Identifying additional factors that worsen COVID-19 patient’s conditions and increase the risk of mortality is essential.