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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