Agile laboratory scoring: Validating the precision and accuracy of Laboratory Markers in predicting hospital-based outcomes in COVID-19 patients

Abstract

This study aimed to identify laboratory predictors of mortality in individuals hospitalized
with COVID-19, to establish a tool for identifying high-risk patients. The research included
all patients admitted to the hospital due to COVID-19, totalling 201 individuals with a
median age of 54.36 ± 13.51 years. Clinical outcomes revealed that 11.2% of patients were
admitted to the Intensive Care Unit (ICU), 9.1% required mechanical ventilation support, and
the overall mortality rate was <10%. Laboratory biomarkers deemed significant for mortality
prediction were incorporated into a risk score calculation. Multivariate logistic regression
model, considering parameters such as haemoglobin, erythrocytes, leukocytes, neutrophils,
lymphocytes, creatinine, and other parameters along with demographic determinants have
been used.