The study aimed to develop and validate a predictive nomogram for assessing the risk of endoscopic hemostasis failure in cirrhotic patients presenting with acute esophagogastric variceal bleeding (EGVB). EGVB is a severe complication of portal hypertension, with a high mortality rate, especially if endoscopic hemostasis fails.
The study aimed to develop and validate a predictive nomogram for assessing the risk of endoscopic hemostasis failure in cirrhotic patients presenting with acute esophagogastric variceal bleeding (EGVB). EGVB is a severe complication of portal hypertension, with a high mortality rate, especially if endoscopic hemostasis fails. Conducted as a retrospective single-center study, 296 patients treated between January 2020 and February 2025 were analyzed. Patients were divided into successful (n=273) and failed (n=23) endoscopic hemostasis groups, with failure defined as rebleeding within five days or inability to control hemorrhage per Baveno VII criteria.
Four independent predictors of failure were identified: Shock Index (SI > 1.2), Red Color (RC) sign, active bleeding during endoscopy, and Child-Turcotte-Pugh (CTP) score. Using LASSO regression and multivariate logistic regression, a nomogram was developed with the formula: Logit (P) = −3.548 + 1.695×SI + 2.303×RC sign + 1.785×Active bleeding + 0.46×CTP score. The nomogram demonstrated excellent predictive performance with an AUC of 0.890, outperforming traditional scoring systems like CTP, MELD, and Rockall.
Risk stratification classified patients into low, medium, and high-risk categories, with failure rates of 0%, 5.7%, and 19.2%, respectively. High-risk patients require ICU-level monitoring and immediate interventions such as secondary endoscopy, balloon tamponade, or TIPS in case of rebleeding. The study highlights the importance of hemodynamic stability (SI), endoscopic findings (RC sign and active bleeding), and liver function (CTP score) in predicting failure. While the nomogram showed promising results, the study’s single-center retrospective design limits external validation. Future research should incorporate imaging modalities and AI-driven analysis for enhanced precision.
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