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首页> 外文期刊>World Journal of Gastroenterology >Accuracy of a predictive model for severe hepatic fibrosis or cirrhosis in chronic hepatitis C.
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Accuracy of a predictive model for severe hepatic fibrosis or cirrhosis in chronic hepatitis C.

机译：慢性丙型肝炎严重肝纤维化或肝硬化的预测模型的准确性。

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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: <10% (low), 10-74% (not diagnostic), 75-90% (high) and >90% (almost absolute). The predicted probabilities were compared with the observed patientso 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 (<10%) probability of severe fibrosis, 33% with a probability ranging from 75% to 90%, and 33% with an uncertain diagnosis (i.e., a probability ranging from 10% to 74%). The observed frequency of severe fibrosis/cirrhosis was within the predefined ranges. CONCLUSION: The model can correctly identify 67% of patients with a high (>75%) or low (<10%) probability of cirrhosis, leaving only 33% of the patients still requiring liver biopsy.
机译：目的：评估在慢性丙型肝炎病毒（HCV）感染中诊断严重纤维化/肝硬化的模型的准确性。方法：该模型基于Bonacini评分（BS：ALT / AST比，血小板计数和INR）和超声检查肝脏表面特征的顺序组合，被用于176例慢性HCV感染患者。假设测试前概率为35％，该模型定义了严重纤维化/肝硬化测试后概率的四个级别：<10％（低），10-74％（非诊断），75-90％（高）和> 90％（几乎绝对）。根据组织学（METAVIR），将预测的概率与观察到的患者分布进行比较。结果：在67名患者中发现了严重的纤维化/肝硬化（38％）。该模型将患者分为三个可比较的组：34％的患者发生严重纤维化的可能性非常高（> 90％）或低（<10％），33％的患者的可能性在75％至90％之间，33％的患者具有严重的纤维化。不确定的诊断（即概率从10％到74％）。观察到的严重纤维化/肝硬化的频率在预定范围内。结论：该模型可以正确识别出67％的肝硬化可能性高（> 75％）或低（<10％）的患者，仅33％的患者仍需进行肝活检。

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