A Retrospective Analysis of the Importance of Biochemical and Hematological Parameters for Mortality Prediction in COVID-19 Cases

Abstract

The recent coronavirus disease 2019 (COVID-19) pandemic has devastated the world's health and economy and has devastatingly affected social and emotional spheres. Although it was the older population who faced the worst, a good number of the younger population also lost their lives. It was very important to predict who will progress to the worst clinical outcome. Consequently, quick and accurate ways of forecasting mortality in COVID-19 cases are essential to save lives. In this study, 11 predictive parameters, namely, Ddimer, creatinine, C-reactive protein (CRP), lactate dehydrogenase (LDH), ferritin, neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), systemic inflammatory index (SII), platelet count, absolute neutrophil count (ANC), and absolute lymphocyte count (ALC), were studied for determining their significance as predictive parameters of mortality in COVID-19-affected patients. MethodsWe conducted a retrospective study of essential parameters, namely, D-dimer, creatinine, CRP, LDH, ferritin, NLR, PLR, SII, platelet count, ANC, and ALC, in confirmed COVID-19 cases for one year between 2020 and 2021. The medical information was obtained from the digital storage sources of the hospital. All cases were segregated into surviving and non-surviving cases. All parameters were collected, results were tabulated, and each individual parameter was then analyzed to see if it showed any significant deviations in nonsurviving cases and could help predict mortalities. Statistical analysis was conducted using the latest version of the Statistical Package for the Social Sciences (SPSS) software (IBM SPSS Statistics, Armonk, NY, USA). ResultsEach of the parameters was individually studied. D-dimer, creatinine, LDH, ferritin, CRP, NLR, PLR, SII, and ANC showed a statistically significant increase in non-surviving cases. Compared to surviving cases, ALC and platelets showed a statistically significant decrease in non-surviving instances. ConclusionAll the studied parameters showed significant deviations in non-surviving cases and could help predict mortalities. This study also stresses the utility of readily available hematological ratios such as NLR and SII for prognosis in COVID-19 subjects.

The role of indices in predicting disease severity and outcomes of multisystem inflammatory syndrome in children

“…[16][17][18] It is imperative to determine the severity of MIS-C disease in the early stages to prevent complications, which can be an important cause of mortality and morbidity for children, and to reduce the mortality rate. Previous studies examined NLR, MLR, and SII indices to predict prognosis in adult patients with COVD-19, [19][20][21][22] but these indices were not adequately evaluated in MIS-C patients. This study aimed to evaluate the role of SII, NLR, MLR, and CAR indices in predicting the severity, treatment, and prognosis of MIS-C, and to determine which of these indices among can be the most effective and useful in predicting outcomes.…”

“…Coronavirus disease (COVID- 19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has high morbidity and mortality. In April 2020, at the peak of the COVID-19 pandemic, a study reported a hyperinflammatory condition similar to Kawasaki disease (KD) and toxic shock syndrome in pediatric patients in the UK.…”