Premier Hospital Surabaya Score: COVID-19 Mortality Score Model Based on Blood Levels of Neutrofil-Lymphocite Ratio, C-Reactive Protein, D-dimer, and Interleukin-6

In order to effectively prevent COVID-19 mortality, accurate prediction is crucial. To address this, we examined the relationship between patient mortality and important clinical factors (NRL, CRP, D-dimer, IL-6). Our study led to the development of the Premier Hospital Surabaya (PHS) Score, which utilizes the analysis of these parameters to correlate with COVID-19 mortality. In this cross-sectional analytic observational study, data were collected via consecutive sampling from eligible subjects' medical records. The initial measurements of NLR, IL-6, CRP, and D-dimer were recorded. Bivariate analysis assessed all variables, and rank Spearman tests were used for each laboratory parameter. Subsequently, logistic regression was employed for multivariate analysis, creating a mortality prediction score model. The cutoff score for early prediction of COVID-19 mortality was determined through the analysis of the Receiver Operating Characteristic (ROC) curve. The laboratory parameters were used to calculate the PHS Score model as follows: PHS Score = NLR score + CRP score + D-dimer score + IL-6 score. The ROC analysis revealed that the PHS score had an AUC of 71.6%. The optimal cutoff point was determined to be 4.5, with a sensitivity of 74.6% and specificity of 65.9%. A PHS Score of ≥4 is indicative of an increased probability of mortality in patients diagnosed with COVID-19. The PHS score derived from the laboratory parameters can aid in predicting the mortality risk during the initial hospital admission. By utilizing this score, healthcare professionals can enhance the management of COVID-19 patients.