These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


PUBMED FOR HANDHELDS

Search MEDLINE/PubMed


  • Title: Proposal of a modified Child-Turcotte-Pugh scoring system and comparison with the model for end-stage liver disease for outcome prediction in patients with cirrhosis.
    Author: Huo TI, Lin HC, Wu JC, Lee FY, Hou MC, Lee PC, Chang FY, Lee SD.
    Journal: Liver Transpl; 2006 Jan; 12(1):65-71. PubMed ID: 16382473.
    Abstract:
    The model for end-stage liver disease (MELD) has a better predictive accuracy for survival than the Child-Turcotte-Pugh (CTP) system and has been the primary reference for organ allocation in liver transplantation. The CTP system, with a score range of 5-15, has a ceiling effect that may compromise its predictive power. In this study, we proposed a refined CTP scoring method and investigated its predictive ability. An additional point was given to patients with serum albumin < 2.3 g/dL, bilirubin > 8 mg/dL or prothrombin time prolongation > 11 seconds. The modified CTP system, containing class D, was compared to the MELD and original CTP system in 436 patients. There was a significant correlation between the MELD and modified CTP score (rho = 0.59, P< 0.001). Using mortality as the endpoint, the area under receiver operating characteristic curve for modified CTP system was 0.895 compared with 0.872 for MELD (P = 0.450) and 0.809 for original CTP system (P < 0.001) at 3 months; the area was 0.890, 0.837 and 0.756, respectively (P = 0.051 and < 0.001, respectively) at 6 months. The risk ratio per unit increase for the modified CTP score was 2.7 and 3.08 at 3 and 6 months respectively (P < 0.001). In conclusion, the modified CTP system can be proposed as an alternative prognostic model for cirrhotic patients. By extending the score range according to the influence of the laboratory-derived variables, the modified CTP system has a better performance than the original system and is as efficient as the MELD for outcome prediction.
    [Abstract] [Full Text] [Related] [New Search]