ArticleFrontiers in medicine2025
Analysis of influencing factors and construction of predictive model for major gastrointestinal bleeding after receiving VTE prophylactic anticoagulants in non-tumor patients.
Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Beyond existing rating scales: development of a novel nomogram for predicting severe clinical bleeding associated with low-molecular-weight heparin in hospitalized medical patients.International journal of clinical pharmacy · 2026Article
- Machine learning-based prediction of gout flares during hospitalization in patients with upper gastrointestinal bleeding: a retrospective cohort study.Frontiers in medicine · 2026Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This study explored the factors associated with major gastrointestinal bleeding (MGB) after the use of prophylactic anticoagulants in patients with high risk of venous thromboembolism (VTE) and developed a predictive model to more accurately identify patients at high risk of MGB. Methods: We collected related data on patients with a high risk of VTE and a low risk of bleeding between January 2020 and December 2024. Propensity score matching (PSM) was conducted to balance the important factors related to the disease status between the non-MGB and MGB groups. By applying univariate and multivariable logistic regression, predictive factors were refined to construct the nomogram. The prediction accuracy of the model was assessed through bootstrapping method (1,000 bootstrap samples), Hosmer-Lemeshow test, and calibration curve analysis. Decision curve analysis (DCA) was also used to assess the clinical applicability of the model. Results: In total, 1,206 eligible patients (1,060 non-MGB vs. 146 MGB) were included. After PSM, the non-MGB group ( Conclusion: The addition of anemia and hypoproteinemia to the Improve-Bleed risk assessment model may help the timely and accurate screening of patients at high risk of MGB. The use of PPIs or H
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