Background: The use of a single abnormal finding on electrocardiography (ECG) is not recommended for stratifying the risk of cardiovascular (CV) events in low-risk general populations because of its low discriminative power. However, the value of a scoring system containing multiple abnormal ECG findings for predicting CV death has not been sufficiently evaluated.
Methods: In a prospective community-based cohort study, 8417 participants without atherosclerotic CV diseases (ASCVDs) and any related symptoms were followed for 18 years. The standard 12-lead ECGs were recorded at baseline and the ECG findings were categorized using the Minnesota code classification. CV deaths were defined as death from myocardial infarction (MI), chronic ischemic heart disease, heart failure, fatal arrhythmia, cerebrovascular event, pulmonary thromboembolism, peripheral vascular disease and sudden cardiac arrest and identified using the Korean National Statistical Office (KOSTAT) database.
Results: In a multivariate Cox proportional hazard (CPH) model, major and minor ST-T wave abnormalities, atrial fibrillation (AF), Q waves in the anterior leads, the lack of Q waves in the posterior leads, high amplitudes of the left and right precordial leads, left axis deviation and sinus tachycardia were associated with higher risks of CV deaths. The ECG score consisted of these findings showed modest predictive values represented by C-statistics that ranged from 0.632 to 760 during the follow-up and performed better in the early follow-up period. The ECG score independently predicted CV death after adjustment for relevant covariates in a multivariate model, and improved the predictive performance of the 10-year ASCVD risk estimator and a model of conventional risk factors including age, diabetes and current smoking. The combined ECG score (Harrell's C-index: 0.852, 95% confidence interval [CI], 0.828-0.876) composed of the ECG score and the conventional risk factors outperformed the 10-year ASCVD risk estimator (Harrell's C-index: 0.806; 95% CI, 0.780-0.833) and the model of the conventional risk factors (Harrell's C-index: 0.841, 95% CI, 0.817-0.865) and exhibited an excellent goodness of fit between the predicted and observed probabilities of CV death.
Conclusions: The ECG score could be useful to predict CV death independently and may add value to the conventional CV risk estimators regarding the risk stratification of CV death in asymptomatic low-risk general populations.
Keywords: Electrocardiography; Minnesota code classification; cardiovascular mortality; low-risk population.
The ECG score based on the Minnesota code classification can independently predict CV death and significantly improve the predictive power of the conventional CV risk estimators in asymptomatic low-risk general population.The combined ECG score comprised the ECG score, age and the presence of diabetes and current smoking predicted CV mortality more accurately than the conventional SV risk estimators.ECG may still be a viable CV risk stratification tool for population-based health screening projects.