A dynamic online nomogram for predicts delayed postoperative bleeding after colorectal polyp surgery

Abstract

Abstract This study aims to analyze the risk factors associated with delayed postoperative bleeding (DPPB) following colorectal polyp surgery, develop a dynamic nomogram and evaluate the model efficacy, provide a reference for clinicians to identify the patients at high risk of DPPB. Retrospective study was done on patients who underwent endoscopic colorectal polypectomy at the First Hospital of Lanzhou University from January 2020 to March 2023. Differences between the group with and without DPPB were compared, and independent risk factors for DPPB occurrence were identified through univariate analysis and combination LASSO and logistic regression. A dynamic nomogram was constructed based on multiple logistic regression to predict DPPB following colorectal polyp surgery. Model evaluation included receiver operating characteristic (ROC), Calibration curve, Decision curve analysis (DCA). DPPB occurred in 38 of the 1544 patients included. multivariate analysis showed that direct oral anticoagulants (DOACs), polyp location in the right hemi colon, polyp diameter, drink, and prophylactic hemoclips were the independent risk factors for DPPB and dynamic nomogram were established. Model validation indicated area under the ROC curve values of 0.936, 0.796, and 0.865 for the training set, validation set, and full set, respectively. The calibration curve demonstrated a strong alignment between the predictions of the column-line diagram model and actual observations. The decision curve analysis (DCA) displayed a significant net clinical benefit across the threshold probability range of 0–100%. The dynamic nomogram aids clinicians in identifying high-risk patients, enabling personalized diagnosis and treatment.

Keywords

• DPPB
• Risk factors
• Dynamic online nomogram
• Prediction model