肝硬化患者肝性脑病风险评估量表模型构建与预测价值研究

Construction of risk assessment model for hepatic encephalopathy in patients with liver cirrhosis and its predictive value

目的 探讨肝硬化患者肝性脑病发生的危险因素,构建风险评估量表模型并分析其预测价值。方法 回顾性分析温州医科大学附属第二医院2021年9月至2022年9月收治的123例单纯肝硬化患者(对照组)与85例肝硬化伴肝性脑病患者(研究组)资料,比较两组患者的一般资料,经二元Logistic回归分析肝性脑病的影响因素,并构建风险评估模型,应用受试者操作特征曲线(receiver operator characteristic,ROC曲线)模型评价肝性脑病患者发生的预测价值。结果单因素与二元Logistic回归分析结果显示,年龄、肝功能Child Pugh分级C级、总胆红素(total bilirubin,TBIL)、尿素氮(blood urea nitrogen,BUN)是肝硬化患者肝性脑病发生的影响因素(P<0.05);依据二元Logistic回归分析结果构建风险评估模型,曲线下面积为0.781(95%CI:0.718~0.844,P<0.05),最大约登指数时肝性脑病发生概率为0.694,对应敏感度与特异性分别为0.694和0.756。结论 年龄、肝功能Child Pugh分级C级、TBIL、BUN是肝硬化患者肝性脑病发生的影响因素,以上述因素为基础构建风险评估模型对肝性脑病发生风险预测价值优异。

Objective To investigate the risk factors of hepatic encephalopathy in patients with liver cirrhosis,construct a risk assessment model,and analyze its predictive value.Methods The data of 123 patients with simple liver cirrhosis and 85 patients with liver cirrhosis and hepatic encephalopathy who were admitted to the hospital from September 2021 by September 2022 were retrospectively analyzed.The general information of two groups of patients were compared,binary Logistic regression analysis was performed to screen the influencing factors of hepatic encephalopathy,and a risk assessment model was constructed based on these factors.The predictive value of this model for hepatic encephalopathy was analyzed using the receiver operator characteristic(ROC)curve.Results Univariate analysis and binary logistic regression analysis results showed that age,Child Pugh grade C,total bilirubin(TBIL),and blood urea nitrogen(BUN)were influencing factors of hepatic encephalopathy(P<0.05).The area under the curve(AUC),maximum Youden index,sensitivity,and specificity of the model for predicting hepatic encephalopathy were 0.781(95%CI:0.718~0.844,P<0.05),0.694,0.694,and 0.756,respectively.Conclusion Age,Child Pugh grade C,TBIL,and BUN are influencing factors of hepatic encephalopathy in patients with liver cirrhosis.The risk assessment model constructed based on these factors helpful for risk prediction of hepatic encephalopathy.