Key result
Adding QT interval, aortic root diameter, and ventricular septal thickness improves cardiovascular risk prediction.
Why the study?
To develop and validate a new CVD prediction model for the general population incorporating both traditional and novel factors.
Does adding electrocardiography (QT interval) and echocardiography (aortic root diameter, ventricular septal thickness) indicators to traditional risk factors improve cardiovascular disease risk prediction in the general population?
Cohort (n=10,349)
Yes
Does adding electrocardiography (QT interval) and echocardiography (aortic root diameter, ventricular septal thickness) indicators to traditional risk factors improve cardiovascular disease risk prediction in the general population?
Adding ECG (QT interval) and echocardiography (aortic root diameter, ventricular septal thickness) parameters to traditional risk factors improves the prediction of incident cardiovascular disease.
OBJECTIVE: To develop and validate a new prediction model for the general population based on a large panel of both traditional and novel factors in cardiovascular disease (CVD). DESIGN AND SETTING: We used a prospective cohort in the Northeast China Rural Cardiovascular Health Study (NCRCHS). PARTICIPANTS: A total of 11,956 participants aged ≥35 years were recruited between 2012 and 2013, using a multistage, randomly stratified, cluster-sampling scheme. In 2015 and 2017, the participants were invited to join the follow-up study for incident cardiovascular events. The loss to follow-up number was 351. At the study's end, we obtained the CVD outcome events for 10,349 participants. PRIMARY AND SECONDARY OUTCOME MEASURES: The prediction model was developed using demographic factors, blood biochemical indicators, electrocardiographic (ECG) characteristics, and echocardiography indicators collected at baseline (Model 1). Framingham-related variables, namely age, sex, smoking, total and high-density lipoprotein cholesterol and diabetes status were used to construct the traditional model (Model 2). RESULTS: For the observed population (n = 10,349), the median follow-up time was 4.66 years. The total incidence of CVD was 1.1%/year, including stroke (n = 342) and coronary heart disease (n = 175). The results of Model 1 indicated that in addition to the traditional risk factors, QT interval (p < 0.001), aortic root diameter (p < 0.001), and ventricular septal thickness (p < 0.001) were predictive factors for CVD. Decision curve analysis (DCA) showed that the net benefit with Model 1 was higher than that of Model 2. CONCLUSION: QT interval from electrocardiography and aortic root diameter and ventricular septal thickness from echocardiography should be included in the CVD risk prediction models.
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Li et al. (2021) conducted a cohort in Cardiovascular disease (n=10,349). Prediction model including ECG and echocardiography indicators (Model 1) vs. Traditional Framingham-related variables model (Model 2) was evaluated on Incident cardiovascular events (stroke and coronary heart disease). Adding QT interval, aortic root diameter, and ventricular septal thickness to traditional risk factors improved cardiovascular disease risk prediction with a higher net benefit.
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