Literature DB >> 9759595

Updating prognosis of cirrhosis by Cox's regression model using Child-Pugh score and aminopyrine breath test as time-dependent covariates.

C Merkel1, A Morabito, D Sacerdoti, M Bolognesi, P Angeli, A Gatta.   

Abstract

BACKGROUND AND AIMS: The determination of aminopyrine breath test on entry into the study was recently shown to improve the accuracy of prediction of death based on the Child-Pugh classification, but the possible usefulness of serial determinations of both parameters has not been assessed. In the present study, we aimed at evaluating whether serial determinations of aminopyrine breath test and Child-Pugh score improve prognostic accuracy in patients with cirrhosis, compared with determinations obtained only on admission. PATIENTS: In 74 patients with liver cirrhosis aminopyrine breath test and Child-Pugh score were obtained upon entry into the study. Patients were followed with sequential aminopyrine breath tests and assessments of the Child-Pugh score every 4-6 months. A total number of 232 determinations were obtained. During follow-up 45 patients died, on average after 12 months of follow-up.
RESULTS: Child-Pugh score improved in the beginning of follow-up, and then remained fairly constant; aminopyrine breath test showed no improvement in the beginning of follow-up, but rather a slowly progressive decline. In patients who died, both the Child-Pugh score and the metabolism of aminopyrine were significantly more impaired in the last year preceding death (p < 0.05). Applying Cox's regression model with time-dependent covariates, Child-Pugh score and aminopyrine breath test were independent significant predictors of survival. The model with time-dependent covariates explained the observed survival much better than the model with time-fixed covariates (chi-sq. explained by regression = 31.45 vs 11.97; d.f. = 2; p = 0.0000001 vs 0.003).
CONCLUSIONS: These data suggest that serial determinations of Child-Pugh score and aminopyrine breath test can be used to efficiently update prognosis of cirrhosis.

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Year:  1998        PMID: 9759595

Source DB:  PubMed          Journal:  Ital J Gastroenterol Hepatol        ISSN: 1125-8055


  1 in total

1.  Models for prediction of mortality from cirrhosis with special reference to artificial neural network: a critical review.

Authors:  Uday Chand Ghoshal; Ananya Das
Journal:  Hepatol Int       Date:  2007-11-27       Impact factor: 6.047

  1 in total

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