Eur J Med Res. 2025 Dec 11. doi: 10.1186/s40001-025-03599-9. Online ahead of print.
ABSTRACT
OBJECTIVES: To develop a nomogram-based risk prediction model utilizing patients’ clinical characteristics for post-endoscopic submucosal dissection hemorrhage, and to evaluate its clinical utility.
METHODS: A total of 250 patients who developed postprocedural hemorrhage after endoscopic submucosal dissection (ESD) for gastrointestinal tumors at our institution (2022-2024) were enrolled. Enrichment criteria included at least one high-risk factor for complications (e.g., lesion size > 10 mm, antithrombotic medication use, or comorbid diabetes/hypertension) or early post-ESD symptoms suggestive of complications. Patients were randomly divided into a training set (n = 175) and a validation set (n = 75) at a 7:3 ratio. In the training set, multivariate logistic regression identified independent prognostic risk factors to construct the nomogram. Model performance was assessed via receiver operating characteristic (ROC) curves and calibration plots, with external validation performed in the validation set.
RESULTS: Hemorrhage occurred in 70/175 cases (40.00%) in the training set and 28/75 (37.33%) in the validation set, with no statistically significant intergroup differences in incidence or baseline characteristics (P > 0.05). Univariate analysis revealed significant disparities between hemorrhage and non-hemorrhage groups in age, hemoglobin, white blood cell count, platelet count, prothrombin time, activated partial thromboplastin time, and fibrinogen (P < 0.05). Multivariate analysis confirmed age, hemoglobin, white blood cell count, platelet count, prothrombin time, activated partial thromboplastin time, and fibrinogen were independent risk factors (P < 0.05). The nomogram demonstrated C-index were 0.861 and 0.841 (validation), and mean absolute errors were 0.151 and 0.171, respectively. AUC values were 0.849 (95% CI 0.778-0.920) and 0.824 (95% CI 0.707-0.941), indicating high predictive accuracy.
CONCLUSIONS: The clinical feature-based nomogram exhibits good predictive performance and reliability in both training and validation cohorts, serving as a valuable tool for prognostic evaluation in gastrointestinal tumor patients who experience post-ESD hemorrhage.
PMID:41382183 | DOI:10.1186/s40001-025-03599-9