Predictive power of Model for End-Stage Liver Disease and Child-Turcotte-Pugh score for mortality in cirrhotic patients.

Aim of the study: To assess the performance of Child-Turcotte-Pugh (CTP) and Model for End-Stage Liver Disease (MELD) scores' kinetics during hospitalization in predicting in-hospital mortality in patients with liver cirrhosis.

Material and methods: One hundred and seventy-four cases of hospitalized liver cirrhosis patients were selected. The diagnosis of cirrhosis was made based on clinical, biochemical, ultrasonic, histological, and endoscopic findings and results. CTP and MELD scores at admission and ΔCTP and ΔMELD were calculated. Univariate and multivariate logistic regression and receiver-operating characteristic (ROC) curve analysis were performed. In the models, odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. The area under the ROC curve (AUC) was used to measure the accuracy. For the optimal cutoff point, sensitivity (SE), specificity (SP), positive predictive value (PPV), and negative predictive value (NPV) were calculated. The Kaplan-Meier method was used to construct survival curves, and the log-rank test was used to compare time to death, with respect to MELD and CTP categories.

Results: Among the assessed scores, the highest area under the ROC curve (AUC) in univariate logistic regression analysis was calculated for ΔMELD ≥ 1, followed by ΔCTP ≥ 1, CTP > 8, and MELD > 17. Based on the selected criteria, multivariate models were created that were characterized by an outstanding ability to predict the in-hospital mortality.

Conclusions: In-hospital mortality is relatively high in patients with liver cirrhosis. The combination of CTP and MELD scoring methods, combined with their kinetics, allows for the prediction of short-term mortality.