Risk Factors for Cardiac Rupture After Acute Myocardial Infarction and Development of a Risk Prediction Model

To investigate the influencing factors for acute myocardial infarction (AMI) complicated by cardiac rupture (CR),evaluate the predictive value of the systemic inflammation response index (SIRI), and construct a clinically practical risk prediction model.

A total of 53 AMI patients complicated with CR admitted to Tianshui First People's Hospital from January 2013 to December 2023 were enrolled as the CR group.During the same period, 159 AMI patients without CR were selected as the control group at a 1:3 ratio, matched for age and sex.Baseline data, clinical indicators, and laboratory test results of patients in both groups were collected, and SIRI was calculated. Lasso regression was used to screen core variables, multivariate Logistic regression analysis was performed to identify independent influencing factors, a nomogram prediction model was constructed based on key variables, and the receiver operating characteristic (ROC) curve was used to evaluate the model's efficacy.

Multivariate Logistic regression analysis showed that admission heart rate (OR = 1.050,95% CI = 1.024-1.075, P < 0.001), Killip classification (OR = 2.092,95% CI = 1.460-2.997, P < 0.001) and SIRI (OR = 1.105,95% CI = 1.022-1.196, P = 0.012) were independent risk factors for CR in AMI patients. Primary PCI (OR = 0.239,95% CI = 0.097-0.589, P = 0.002) and taking ACEI / ARB drugs within 24 hours (OR = 0.173,95% CI = 0.060-0.500, P = 0.001) were protective factors. The ROC curve model constructed based on the above five indicators has an area under the curve (AUC) of 0.885.

Admission heart rate, Killip classification, and systemic inflammatory response index are independent risk factors for AMI with CR. Primary PCI and the administration of ACEI/ARB within 24 hours of admission were identified as protective factors against CR. The nomogram model demonstrated good predictive value for the occurrence of cardiac rupture in patients with AMI.