1. External validation and comparison of six prognostic models in a prospective cohort of HBV-ACLF in China.
- Author
-
Shen Y, Liu YM, Wang B, Zhu YG, Wang YY, Wang XL, Ji JL, Shao JG, Qin Y, and Qin G
- Subjects
- Acute-On-Chronic Liver Failure blood, Acute-On-Chronic Liver Failure complications, Adult, Age Factors, Aged, China, Cohort Studies, Discriminant Analysis, End Stage Liver Disease, Female, Hepatitis B, Chronic blood, Hepatitis B, Chronic complications, Humans, Male, Middle Aged, Prognosis, Prospective Studies, Severity of Illness Index, Sodium blood, Young Adult, Acute-On-Chronic Liver Failure mortality, Hepatitis B, Chronic mortality
- Abstract
Unlabelled: Background. Acute-on-chronic liver failure has high mortality. Currently, robust models for predicting the outcome of hepatitis B virus (HBV)-associated ACLF are lacking., Aim: To assess and compare the performance of six prevalent models for short- and longterm prognosis in patients with HBV-ACLF., Material and Methods: The model for end-stage liver disease (MELD), MELD sodium (MELD-Na), MELD to sodium ratio (MESO), integrated MELD, Child-Turcotte-Pugh (CTP), and modified CTP (mCTP) were validated in a prospective cohort of 232 HBV-ACLF patients. The six models were evaluated by determining discrimination, calibration and overall performance at 3 months and 5 years., Results: According to the Hosmer-Lemeshow tests and calibration plots, all models could adequately describe the data except CTP at 3 months. Discrimination analysis showed that the iMELD score had the highest AUC of 0.76 with sensitivity of 62.6% and specificity of 80.2% for an optimal cut-off value of 52 at 3 months. It also had the highest AUC of 0.80 with sensitivity of 89.9% and specificity of 48.2% for an optimal cut-off value of 43 at 5 years. The overall performance of iMELD, assessed with Nagelkerke's R2 and the Brier score, was also the best among the six models., Conclusion: Integrated MELD may be the best model to predict short- and long-term prognosis in patients with HBV-ACLF.
- Published
- 2016
- Full Text
- View/download PDF