医学
肝性脑病
内科学
接收机工作特性
乙型肝炎病毒
队列
逻辑回归
肝衰竭
胃肠病学
肝病
凝血酶原时间
人口
病毒
免疫学
肝硬化
环境卫生
作者
Chunhua Hu,Na Jiang,Jie Zheng,Chenxia Li,Huihong Huang,Juan Li,Hongbing Li,Zhijie Gao,Nan Yang,Qi Xi,Jing Wang,Zitong Liu,K Jaya Rao,Heping Zhou,Tianhui Li,Yi Chen,Yuelang Zhang,Jian Yang,Shihua Zhao,Yingli He
摘要
Hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) is a life-threatening disease with high short-term mortality. Early and accurate prognosis is significant for clinical decisions, in which liver volume (LV) imparts important information. However, LV has not been considered in current prognostic models for HBV-ACLF.Three hundred and twenty-three patients were recruited to the deriving cohort, while 163 were enrolled to validation cohort. The primary end-point was death within 28 days since admission. Estimated liver volume (ELV) was calculated by the formula based on healthy population. Logistic regression was used to develop a prediction model. Accuracy of models were evaluated by receiver operating characteristic (ROC) curves.The ratio of LV to ELV (LV/ELV%) was significantly lower in non-survivors, and LV/ELV% ≤82% indicated poor prognosis. LV/ELV%, Age, prothrombin time (PT), the grade of hepatic encephalopathy (HE), ln-transformed total bilirubin (lnTBil), and log-transformed HBV DNA (Log10 HBV DNA) were identified as independent predictors to develop an LV-based model, LEAP-HBV. The mean area under the ROC (AUC) of LEAP-HBV was 0.906 (95% CI, 0.904-0.908), higher than other non-LV-based models.Liver volume was an independent predictor, and LEAP-HBV, a prediction model based on LV, was developed for the short-term mortality in HBV-ACLF. This study was registered on ClinicalTrails (NCT03977857).
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