Abstract P260: Can Metabolic Syndrome Predict the Incidence of Silent Myocardial Infarction? An Analysis From the Atherosclerosis Risk in Communities (ARIC) Study

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Abstract

Introduction: Diabetes patients are at risk for clinical Myocardial Infarction (MI) and have a larger proportion being silent Myocardial Infarction. However, less is known about the impact of Metabolic Syndrome (MetS, also known as prediabetes) on the incidence of silent MI. Here, we studied whether the degree of MetS severity can be predictive for future risk of silent MI.

Methods: 12,527 ARIC study participants who are free of coronary heart diseases (CHD) and diabetes at baseline (1987-1989) were included for the analysis. Silent MI was determined by ECG serial changes of MI without prior clinical history of MI. A continuous MetS severity score was formulated from the integration of MetS components to assess its prediction for future silent MI and clinical MI.

Results and Conclusions: 458 participants (3.7%, 458 of 12,527) developed clinical MI and 87 (0.7%, 87 of 12,527) were diagnosed with silent MI until ARIC visit 4 (1996-1998). Within the 10 years follow-up period, gender, smoking status, MetS components (waist circumference, blood pressure, HDL cholesterol) and the integrated MetS severity score were identified as significant risk factors for the incidence of both silent MI and clinical MI. Participants with MetS had a significant adjusted HR for incident silent MI (HR = 1.98, 95% CI: [1.30, 3.02], p=0.0015) as compared to clinical MI (HR = 1.67, 95% CI: [1.39, 2.00], p<0.0001). The 10-year risk scoring equations of silent MI and clinical MI were constructed as a multivariate predictive tool based on MetS severity score. In conclusion, higher MetS severity score is associated with further risk of both clinical and silent MI, identifying the potential clinical application of MetS severity score in MI prevention.

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