Construction and validation of risk prediction model for gastrointestinal bleeding in patients after coronary artery bypass transplantation

Abstract

Abstract Objective: This study aimed to develop a risk prediction model for gastrointestinal bleeding in patients after coronary artery bypass grafting (CABG) and assess its accuracy. Methods: A retrospective analysis was conducted on 232 patients who underwent CABG under general anesthesia at our hospital between January 2022 and December 2022. The patients were divided into two groups: the gastrointestinal bleeding group (n=52) and the group without gastrointestinal bleeding (n=180). The independent risk factors for gastrointestinal bleeding in post-CABG patients were analyzed using χ2 test, t test, and Logistic multivariate regression analysis. A prediction model was established based on the identified risk factors. To verify the accuracy of the prediction model, a verification group of 161 patients who met the criteria from January to June 2023 was selected, and the Bootstrap method was used for internal validation. The discrimination of the prediction model was evaluated using the area under the curve (AUC), where a higher AUC indicates a stronger discrimination effect of the model. Results:The study developed a risk prediction model for gastrointestinal bleeding after coronary artery bypass grafting (CABG) surgery. The model identified four independent risk factors: duration of stay in the intensive care unit (OR=0.761), cardiopulmonary bypass time (OR=1.019), prolonged aortic occlusion time (OR=0.981), and re-operation for bleeding (OR=0.180). Based on these factors, an individualized risk prediction model was constructed. The C-index values of the modeling group and the verification group were 0.805 [95% CI (0.7303-0.8793)] and 0.785 [95% CI (0.6932-0.8766)], respectively, indicating good accuracy and discrimination. The calibration and standard curves showed similar results, further supporting the accuracy of the risk prediction model. Conclusion:In conclusion, ICU time, cardiopulmonary bypass time, aortic occlusion time, and re-operation for bleeding are identified as independent risk factors for gastrointestinal bleeding in patients after CABG surgery. The risk prediction model developed in this study demonstrates strong predictive performance, offering valuable insights for clinical medical professionals in evaluating gastrointestinal complications in CABG patients.