Accuracy of a predictive model for severe hepatic fibrosis or cirrhosis in chronic hepatitis C

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AIM: To assess the accuracy of a model in diagnosing severe fibrosis/cirrhosis in chronic hepatitis C virus (HCV)infection.METHODS: The model, based on the sequential combination of the Bonacini score (BS: ALT/AST ratio,platelet count and INR) and ultrasonography liver surface characteristics, was applied to 176 patients with chronic HCV infection. Assuming a pre-test probability of 35%,the model defined four levels of post-test probability of severe fibrosis/cirrhosis: 90% (almost absolute).The predicted probabilities were compared with the observed patients distribution according to the histology (METAVIR).RESULTS: Severe fibrosis/cirrhosis was found in 67 patients (38%). The model discriminated patients in three comparable groups: 34% with a very high (>90%)or low (75%) or low (
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