A revised model for end-stage liver disease optimizes prediction of mortality among XXXX awaiting liver transplantation.

@entity1 @entity648 @entity1372 @entity3851 @entity1011
BACKGROUND _ AIMS: The @entity3851 ( @entity3851 ) was originally developed based on data from @entity1 who underwent the transjugular intrahepatic portosystemic shunt procedure. An updated @entity3851 based on data from @entity1 awaiting liver transplantation should improve mortality prediction and allocation efficiency. METHODS: Wait-list data from adult primary liver transplantation candidates from the Organ Procurement and Transplantation Network were divided into a model derivation set (2005-2006; n=14,214) and validation set (2007-2008; n=13,945). Cox regression analysis was used to derive and validate an optimized model that updated coefficients and upper and lower bounds for @entity3851 components and included serum levels of @entity1372 . Main outcomes measure was ability to predict 90-day mortality of @entity1 on the liver transplantation wait list. RESULTS: Optimized @entity3851 score updated coefficients and implemented new upper and lower bounds for @entity1011 (0.8 and 3.0 mg/dL, respectively) and international normalized ratio (1 and 3, respectively). Serum @entity1372 concentrations significantly predicted mortality, even after adjusting for the updated @entity3851 model. The final model, based on updated fit of the 4 variables (ie, @entity648 , @entity1011 , international normalized ratio, and @entity1372 ) had a modest yet statistically significant gain in discrimination (concordance: 0.878 vs 0.865; P<.01) in the validation dataset. Utilization of the new score could affect up to 12% of @entity1 (based on changed score for 459 of 3981 transplants in the validation set). CONCLUSIONS: Modification of @entity3851 score to update coefficients, change upper and lower bounds, and incorporate serum @entity1372 levels improved wait-list mortality prediction and should increase efficiency of allocation of donated livers.
