Development and validation of an AMR-based predictive model for post-PCI upper gastrointestinal bleeding in NSTEMI patients

Background: Upper gastrointestinal bleeding (UGIB) is a common complication in patients with non-ST-segment elevation myocardial infarction (NSTEMI) after percutaneous coronary intervention (PCI), and the aim of our study is to construct a nomogram for predicting the occurrence of UGIB within 1 year after PCI in NSTEMI patients. Methods: In this study, 784 patients with NSTEMI after PCI in the Affiliated Hospital of Xuzhou Medical University between September 1, 2017 and August 31, 2019 were included as the training group, and 336 patients from the East Affiliated Hospital of Xuzhou Medical University were included as the external validation group. Classical regression methods were combined with a machine learning model to identify the independent risk factors. These factors based on multivariate logistic regression analysis were then utilized to develop a nomogram. The performance of the nomogram was evaluated using the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis (DCA). Results: The nomogram consisted of six independent predictors, including HASBLED, triglyceride glucose index, alcohol drinking, red blood cell count, use of proton pump inhibitor, and angiographic microvascular resistance of culprit vessel. Training and validation groups accurately predicted the occurrence of UGIB (AUC, 0.936 and 0.910). The calibration curves showed that the nomogram agreed with the actual observations and the DCA also demonstrated that the nomogram was applicable in the clinic. Conclusion: We developed a simple and effective nomogram for predicting the occurrence of UGIB within 1 year in NSTEMI patients after PCI based on angiographic microvascular resistance.