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肝硬化上消化道出血患者预后的列线图预测模型构建
作者:安江科  郭楠楠  段树静 
单位:石家庄平安医院 重症医学科, 河北 石家庄 050000
关键词:肝硬化 上消化道出血 预后 列线图模型 
分类号:R573.2;R575.2
出版年·卷·期(页码):2023·51·第三期(289-294)
摘要:

目的:构建预测肝硬化上消化道出血(UGH)患者预后的列线图模型,并检验其预测效能。方法:回顾性分析2017年4月至2022年4月本院收治的435例肝硬化UGH患者的临床资料,根据治疗后1个月内生存情况分成生存组和死亡组。对两组行单因素分析及Logistic回归分析,确定其影响因素后构建列线图模型,并通过受试者工作特征(ROC)曲线下面积(AUC)和H-L拟合优度对模型的区分度和精准度予以验证。结果:435例患者中,49例死亡,生存386例;生存组和死亡组出血原因、出血量、治疗后72 h内再出血比例、Child-Pugh分级、并发肝性脑病比例、血清白蛋白水平比较差异有统计学意义(P<0.05);Logistic回归分析结果显示,肝硬化UGH患者预后的影响因素主要有食管胃底静脉曲张(EGV)、出血量≥500 ml、治疗后72 h内再出血、Child-Pugh分级为C级、并发肝性脑病等5项(P<0.05);ROC曲线分析结果显示,构建的预测肝硬化UGH患者预后的列线图模型区分度(AUC为0.778,95%CI 0.709~0.848)及精准度(拟合优度H-L检验χ2=7.136,P=0.539)较高。结论:基于EGV、出血量≥500 ml、治疗后72 h内再出血、Child-Pugh分级为C级、并发肝性脑病等5项因素构建的列线图预测模型可较好地预测肝硬化UGH患者预后。

Objective: To construct a nomogram model for predicting the prognosis of patients with liver cirrhosis upper gastrointestinal hemorrhage (UGH), and to test its predictive performance. Methods: The clinical data of 435 patients with liver cirrhosis UGH admitted to our hospital from April 2017 to April 2022 were retrospectively analyzed, and they were divided into survival group and death group according to the survival condition within 1 month after treatment. The univariate analysis and Logistic regression analysis of the two groups were conducted, the nomogram model was established after determining the influencing factors, and the differentiation and accuracy of the model were verified by the area under receiver operating characteristic curve (AUC) and H-L goodness of fit. Results: Among 435 patients, 49 died and 386 survived; there were obvious differences in the cause of bleeding, the amount of bleeding, the proportion of rebleeding within 72 hours after treatment, the Child-Pugh classification, the proportion of complicated hepatic encephalopathy, and the level of serum albuminbetween the survival group and the death group (P<0.05); Logistic regression analysis showed that the prognostic factors of patients with liver cirrhosis UGH mainly included esophagealand gastric varices(EGV), bleeding volume ≥500 ml, rebleeding within 72 hours after treatment, Child-Pugh grade of grade C, complicated with hepatic encephalopathy (P<0.05); the receiver operating characteristic curve analysis results showed that the constructed nomogram model for predicting the prognosis of patients with liver cirrhosis UGH had higher discrimination (AUC=0.778, 95%CI 0.709-0.848) and accuracy (H-L test χ2=7.136, P=0.539). Conclusion: The nomogram prediction model constructed based on five factors including EGV, bleeding volume ≥500 ml, rebleeding within 72 hours after treatment, Child-Pugh grade of grade C, and complicated with hepatic encephalopathy can better predict the prognosis of patients with liver cirrhosis UGH.

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