A Novel Predictor Compared to the Model for End-Stage Liver Disease (MELD) and Child-Turcotte-Pugh (CTP) Scores for Predicting 30-Day Mortality in Patients With Liver Cirrhosis

Background Liver cirrhosis (LC) is characterized by the development of fibrosis and nodules within the liver, leading to progressive liver dysfunction. The mortality rate associated with LC has consistently remained high over the years. Prognostic tools such as the Child-Turcotte-Pugh (CTP) score and the Model for End-Stage Liver Disease (MELD) score are commonly used to predict mortality and assess the severity of LC. Both scoring systems rely on laboratory parameters, including serum albumin, total bilirubin, and international normalized ratio (INR) levels. However, the CTP score interpretation can be variable, and INR testing is not routinely performed in many clinical settings, which may limit its utility. This study aims to assess the MELD and CTP scores, along with a new predictive tool, in estimating 30-day mortality for patients with LC. Methodology This retrospective cohort study focuses on patients diagnosed with LC at Ngoerah Central General Hospital. Physical examination data and laboratory ratios, including neutrophil-to-lymphocyte ratio (NLR), aspartate transaminase (AST) to alanine transaminase (ALT) ratio (de Ritis), neutrophil-to-lymphocyte-to-albumin (NLA) ratio, albumin bilirubin index (ALBI), and blood urea nitrogen-to-albumin ratio (BAR), were collected from medical records. Optimal cutoff values were established using receiver operating characteristic (ROC) curves. Survival analysis was performed using the Kaplan-Meier method, and multivariate Cox regression was employed to determine the hazard ratio (HR) for each variable that was statistically significant as a predictor of 30-day mortality. Results In this study, a total of 140 samples were analyzed. Kaplan-Meier analysis revealed that hepatic encephalopathy (HE) met the criteria, while interaction analysis testing was required for other variables. Results from the multivariate Cox regression interaction model showed that ALBI-HE (HR = 1.743, 95% confidence interval [CI] 1.102-2.759, <i>P</i> = 0.018), BAR-HE (HR = 0.577, 95% CI 0.367-0.905, <i>P</i> = 0.017), and NLA-HE (HR = 0.332, 95% CI 0.195-0.563, <i>P</i> < 0.001) were significant independent predictors of 30-day mortality in LC. CTP, MELD, NLR, and de Ritis did not demonstrate statistical significance. ALBI-HE emerged as the strongest predictor based on its HR. Conclusions ALBI-HE, BAR-HE, and NLA-HE have emerged as novel predictors for assessing 30-day mortality in LC. ALBI-HE is the strongest predictor of 30-day mortality in LC.