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

Area of Science:

• Cardiology
• Internal Medicine
• Medical Research

Background:

• Acute myocardial infarction (AMI) is a leading cause of cardiovascular mortality.
• Cardiac rupture (CR) is a severe complication of AMI, significantly increasing mortality.
• Identifying predictive factors for CR is crucial for timely intervention.

Purpose of the Study:

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

Main Methods:

• A case-control study involving 53 AMI patients with CR and 159 without CR.
• Collected baseline data, clinical indicators, and laboratory results, including SIRI calculation.
• Utilized Lasso regression, multivariate Logistic regression, and ROC curve analysis to identify risk factors and build a predictive model.

Main Results:

• Admission heart rate, Killip classification, and SIRI were identified as independent risk factors for CR.
• Primary PCI and ACEI/ARB administration within 24 hours were protective factors against CR.
• The constructed nomogram prediction model achieved an AUC of 0.885.

Conclusions:

• Admission heart rate, Killip classification, and SIRI are significant independent risk factors for CR in AMI.
• Early primary PCI and ACEI/ARB treatment are protective against CR.
• The developed nomogram model shows strong predictive value for CR in AMI patients.