Development of a prediction model for exercise tolerance decline in the exercise assessment of patients with acute myocardial infarction undergoing percutaneous coronary intervention revascularization in the acute phase.

Background: Early cardiopulmonary exercise test (CPET) may predict the prognosis of patients with acute myocardial infarction (AMI) after percutaneous coronary intervention (PCI). However, data from CPET to assess the exercise capacity of patients with AMI PCI are still scarce. This study aimed to evaluate the safety of the CPET and assess the predictors and clinical influence of exercise capacity measured by CPET in patients with AMI within 1 week after PCI. Methods: A total of 275 patients with AMI who underwent PCI in the acute phase were selected. Reduced exercise capacity was defined as peak oxygen uptake (VO Results: The median time of CPET in all patients was 5 days after PCI. Among the 275 patients, exercise tolerance decreased in 90 cases (32.72%). Multivariate logic analysis showed that E/e', age, glycosylated hemoglobin, and estimated glomerular filtration rate (eGFR) were independent predictors of early exercise capacity reduction in these patients. Utilizing the correlation coefficients from pre-assessment clinical and CPET indicators within the logistic regression framework, we constructed a nomogram model to forecast the diminishing exercise tolerance in AMI patients. The predictive accuracy of this model, as indicated by a C-index of 0.771 and an area under the receiver operating characteristic (ROC) curve of 0.771 (95% CI: 0.710-0.832), demonstrates its potential as a robust tool in clinical settings. During a follow-up of 24 months, the incidence of clinical outcomes in patients with low exercise tolerance was significantly higher than that in patients with normal exercise tolerance, among which all-cause mortality and reinfarction were statistically different (P=0.009 and P=0.043). Conclusions: The reduced exercise capacity in patients with AMI after initial PCI is related to age, diastolic dysfunction, renal function, and blood glucose control, which may lead to poor clinical prognosis. The nomogram prediction model performed well in predicting the declining exercise tolerance of patients with AMI.