ArticleBMC gastroenterology2024
Construction and validation of a predictive model for the risk of rebleeding in patients with esophageal and gastric varices hemorrhage.
Article in BMC gastroenterology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Development and validation of a score model for predicting the risk of first esophagogastric variceal hemorrhage and mortality in patients with hepatocellular carcinoma.Annals of medicine · 2025Article
- Development and validation of machine learning models to predict esophagogastric variceal rebleeding risk in HBV-related cirrhosis after endoscopic treatment: a prospective multicenter study.EClinicalMedicine · 2025Article
- Development and validation of a predictive model for 90-day mortality risk after discharge in patients with cirrhosis and esophagogastric variceal bleeding.Scientific reports · 2025Article
- Development, validation, and web deployment of a rebleeding risk prediction model for acute non-variceal upper gastrointestinal bleeding in a Chinese population.Frontiers in medicine · 2025Article
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Authors and funding
3 authors.
Funding
Abstract
background and purposeEsophageal and gastric varices hemorrhage (EGVH) is a life-threatening condition with the 6-week mortality rate of 15-25%. Up to 60% of patients with EGVH may experience rebleeding with a mortality rate of 33%. The existing scoring systems, such as RS scoring system (Rockall score, RS) and GBS scoring system (Glasgow-Blatchford score, GBS), have limitations in predicting the risk of rebleeding. Our study was to construct and validate a novel predictive model for the risk of rebleeding in patients with EGVH and to compare the predictive power of the predictive model with GBS and pRS.
methodsData of patients with EGVH was collected in the First Affiliated Hospital of Dalian Medical University from January 2016 to June 2020. Binary logistic and stepwise regression was performed to construct a predictive model. We compared the predictive power of the new predictive model to the GBS and pRS scoring systems.
resultsClinical data from a total of 265 patients with EGVH was collected. Six factors including systolic blood pressure, transfusion requirement, CA199, platelet count, upper esophageal varices and severity of esophageal varices were included in our new predictive model. The AUCs of the specificity of the predictive model, GBS and pRS are 0.82, 0.60 and 0.56.
conclusionThis study successfully constructed a predictive model for the risk of rebleeding in patients with EGVH. This predictive model demonstrated higher predictive ability than pRS and GBS scoring systems for assessing rebleeding risk in EGVH patients.
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