Establishment and evaluation of an early prediction model of hepatorenal syndrome in patients with decompensated hepatitis B cirrhosis

建立和评价失代偿期乙型肝炎肝硬化患者肝肾综合征早期预测模型

阅读:1

Abstract

BACKGROUND AND AIM: In China, hepatorenal syndrome is a serious complication in the decompensated stage of hepatitis B cirrhosis, which requires early clinical intervention, so the early diagnosis of hepatorenal syndrome is crucial. This study establishes a new predictive model based on serum biomarkers for the early diagnosis of hepatorenal syndrome. METHODS: Patients with decompensated hepatitis B cirrhosis who met the inclusion and exclusion criteria were retrospectively enrolled. Patients were randomly assigned to the training dataset and validation dataset at a 7:3 ratio. Univariate and multivariate logistic regression analyses were used to screen the risk factors for hepatorenal syndrome. The identified risk factors were used to establish and verify a model. RESULTS: This study included 255 patients with decompensated hepatitis B cirrhosis, including 184 in the training group and 71 in the validation group. The multivariate logistic regression model was established in the training group and verified in the validation group. Logistic regression showed that hemoglobin (OR 0.938, 95% CI 0.908-0.969), total bilirubin (OR 1.014, 95% CI 1.008-1.021) and creatinine (OR 1.079, 95% CI 1.043-1.117) were independent risk factors for hepatorenal syndrome (P < 0.05). These were used to establish the model. In the training group and the validation group, the area under the ROC curve of the nomogram for the diagnosis of hepatorenal syndrome was 0.968 and 0.980, respectively. CONCLUSION: The three serum biomarkers, including hemoglobin, total bilirubin and creatinine, can be used as independent early predictors of hepatorenal syndrome in patients with decompensated hepatitis B cirrhosis.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。