ArticleFrontiers in pediatrics2026
Construction and validation of a prognostic model for children with acute upper gastrointestinal bleeding.
Article in Frontiers in pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
Background: Gastrointestinal bleeding (GIB) is a common symptom of the pediatric digestive system, with acute upper gastrointestinal bleeding (AUGIB) being extremely dangerous for children. In the present study, we established a risk prediction model for the prognosis of children with AUGIB and provided a new method for early identification of poor prognosis, thereby reducing the disease burden. Methods: Binary logistic regression analysis was conducted to identify independent risk factors influencing the outcomes of children with AUGIB. The receiver operating characteristic curve (ROC) was generated to assess the predictive efficacy of these risk factors. A nomogram prediction model was constructed, and its performance was evaluated using the consistency index (C-index) and calibration curve. Decision curve analysis (DCA) was applied to estimate the clinical benefits of the intervention. Results: A total of 372 children who were diagnosed with AUGIB and met the inclusion criteria were enrolled in the study. Neutrophil to leukocyte ratio (NLR), platelet to lymphocyte ratio (PLR), hemoglobin (Hb), high-sensitivity C-reactive protein (hsCRP), and activated partial thromboplastin time (APTT) are independent influencing factors for the outcomes of AUGIB in children. The nomogram model was constructed by including the above independent influencing factors; the consistency index was 0.945 [95 confidence interval (CI): 0.931-0.959]. The DCA was used to assess the prediction performance of the model to obtain net clinical benefits. Conclusion: A preoperative serum test was an effective and objective method to predict the prognosis of children with AUGIB. The established prognostic risk prediction model had a good prediction effect; it could provide a reference to clinically assess the risk of poor prognosis in children with AUGIB.
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