MELD >or= 18 and TC

year, the iMELD still had the highest AUC (0.783), the difference between the iMELD and MELD was statistically significant (P < 0.05). Survival curves showed that the three new models were all clearly discriminated the patients who survived or died in short-term as well as intermediate-term (P < 0.001 INTRODUCTIONThe model for end-stage liver disease (MELD) was developed as a prognostic model of short-term mortality in patients with cirrhosis treated with transjugular intrahepatic portosystemic shunt (TIPS) [1] . The scoring system has been widely applied in recent years and shown to predict mortality across a broad spectrum of liver diseases in most studies. But, there is not any parameter correlated with complications of cirrhosis in this formula. Its ability of prognosis is decreased. Some studies have indicated that serum sodium is the independent predictor of mortality in patients with cirrhosis [2,3] . And the incorporation of Na into the MELD may enhance its prognostic accuracy [4,5] . Then some scholars had successively introduced three new mathematical equations based on both MELD and Na, Abstract AIM: To investigate the prognostic value of the model for end-stage liver disease (MELD) and three new MELD-based models combination with serum sodium in decompensated cirrhosis patients-the MELD with the incorporation of serum sodium (MELD-Na), the integrated MELD (iMELD), and the MELD to sodium (MESO) index. METHODS: A total of 166 patients with decompensated cirrhosis were enrolled into the study. MELD, MELDNa, iMELD and MESO scores were calculated for each patient following the original formula on the first day of admission. All patients were followed up at least 1 year. The predictive prognosis related with the four models was determined by the area under the receiver operating characteristic curve (AUC) of the four parameters. Kaplan-Meier survival curves were made using the cut-offs identified by means of receiver operating characteristic (ROC). RESULTS: Out of 166 patients, 38 patients with significantly higher MELD-Na (28.84 ± 2.43 vs 14.72 ± 0.60), iMELD (49.04 ± 1.72 vs 35.52 ± 0.67), MESO scores (1.59 ± 0.82 vs 0.99 ± 0.42) compared to the survivors died within 3 mo (P < 0.001). Of 166 patients, 75 with markedly higher MELD-Na (23.01 ± 1.51 vs 13.78 ± 0.69), iMELD (44.06 ± 1.19 vs 34.12 ± 0.69), MESO scores (1.37 ± 0.70 vs 0.93 ± 0.40) than the survivors died within 1 year (P < 0.001). At 3 mo of enrollment, the iMELD had the highest AUC (0.841), and was followed by the MELD-Na (0.766), MESO (0.723), all larger than MELD (0.773); At 1

Noninvasive prediction of large esophageal varices in liver cirrhosis patients Abstract Purpose: Esophageal varices are a dangerous complication of liver cirrhosis. e development of cost e ective, noninvasive means for prediction of large esophageal varices could reduce the use of upper gastrointestinal endoscopy in variceal screening and also provide an alternative way to con rm the results of conventional endoscopic diagnosis. Previously proposed predictive models are neither sensitive nor speci c.Methods: A retrospective study based on a group of 104 liver cirrhosis patients was performed. Multiple statistical approaches were used to evaluate the association of large esophageal varices with 20 individual and six compound clinical laboratory variables. A new predictive model was developed.Results: Univariate analysis suggested that eight out of 26 variables were signi cantly associated with large esophageal varices. Further stepwise logistic regression eventually identied three variables (hemoglobin level, portal vein diameter and the ratio of platelet count/ spleen diameter) that contributed signi cantly to the nal regression model. Receiver operating characteristic (ROC) curve analysis showed that this new regression model achieved 77.8% and 72% of diagnostic sensitivity and speci city, respectively, for the prediction of large esophageal varices. In our study group, its diagnostic accuracy (AUROC=0.814) was found to be signi cantly higher than six predictive models previously published.Conclusions: No single variable o ers self-su cient predictive function for large esophageal varices. A comprehensive model using multiple variables signi cantly improves the predictive accuracy in screening the most at risk patients with potential variceal hemorrhage.

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