The relationship between subclinical atherosclerosis and electrocardiographic abnormalities as biomarkers of cardiovascular risk.

ABSTRACT

Electrocardiographic findings indicating myocardial disease, such as left ventricular hypertrophy or ST-T wave abnormalities, or the presence of coronary artery calcium, indicating atherosclerotic coronary artery disease, are both biomarkers of future cardiovascular (CV) risk. Although the risk factors for myocardial and coronary artery disease are similar, their concomitant expression has implications for CV disease screening and prevention programmes. The relationship between the resting 12-lead ECG and subclinical atherosclerosis measured as coronary artery calcium (CAC) with electron beam tomography was examined in 937 healthy participants (aged 40-50 years) enrolled in a CV risk screening study. Electrocardiograms and CAC were interpreted in blinded fashion, using standard criteria. An abnormal ECG was coded in 268 (28.6%) participants, most commonly left ventricular hypertrophy (3.1%), delayed precordial R wave transition (5.7%), T-wave abnormalities (10.0%) and intraventricular conduction delay (10.4%). Although abnormal ECG findings were associated with CV risk variables, the prevalence of any CAC was similar in subjects with any ECG finding (43 of 268, 16.0%) compared with those with normal ECGs (125 of 669, 18.7%, p =NS). In a logistic model controlling for CV risk factors including systolic blood pressure, low-density lipoprotein cholesterol (LDL-C), body mass index (BMI), glycosylated haemoglobin, race, age and gender, significant associations with CAC were found for LDL-C, race and BMI. There was no significant relationship between CAC and ECG abnormalities (odds ratio 0.80, 95% confidence interval 0.54-1.20). In conclusion, electrocardiographic abnormalities and subclinical calcified atherosclerosis were not significantly associated with each other in this middle-aged screening population. This suggests these two biomarkers may be complementary towards broader detection of latent CV risk.