Novel Analysis of Coronary Angiography in Predicting the Formation of Ventricular Aneurysm in Patients With Acute Myocardial Infarction After Percutaneous Coronary Intervention

BACKGROUND: Ventricular aneurysm (VA) is a serious complication of acute myocardial infarction (AMI), with a very poor prognosis. Early-stage prophylactic treatment is effective in preventing the formation of VAs. However, the existing predictive models for VA formation lack the sensitivity and specificity necessary for evaluating patients with MI. This study aimed to explore the potential use of coronary angiography and establish a more precise prediction model for VA in patients with MI. METHODS: Patients with VA (n = 52) admitted to our medical center between June 2020 and July 2021 with previous emergency percutaneous coronary intervention for AMI were retrospectively included in this database study. Controls that matched 4:1 with the VA cases during the same period were enrolled. The baseline characteristics and coronary angiograms of the enrolled individuals were obtained from the electronic medical record system. The curve length of the distance from the main criminal lesion to its ostia (DLO) and distal (DLD) in the coronary artery were measured with ImageJ. Binary logistic regression analysis was used to identify the predictive factors. The model performance was evaluated by receiver operating characteristic curve analysis. RESULTS: Binary analysis revealed maximum serum cardiac troponin I level (odds ratio [OR] = 1.046, 95% confidence interval [CI] = 1.027–1.066, P < 0.001), serum brain natriuretic peptide level (OR = 1.001, 95% CI = 1.000–1.002, P = 0.007), left anterior descending artery as the culprit lesion (OR = 5.091, 95% CI = 2.080–12.457, P < 0.001), and that single-vessel disease (OR = 1.809, 95% CI = 0.967–3.385, P < 0.001), stenosis in the main lesion (OR = 1.247, 95% CI = 1.173–1.327, P < 0.001), DLO (OR = 1.034, 95% CI = 1.019–1.049, P < 0.001), DLD (OR = 1.061, 95% CI = 1.043–1.079, P < 0.001), and DLD/DLD (OR = 0.033, 95% CI = 0.010–0.117, P < 0.001) were the independent variables for predicting VA formation in MI patients. CONCLUSION: Our study first used quantified information of coronary lesions to establish a predictive model and proved that a longer DLD had the greatest potential in predicting the incidence of VA. Its related parameters including DLO and DLO/DLD ratio were also correlated with the incidence of VA. These findings may provide a new reference for the early identification of high-risk MI patients and preventing VA.