Association Between Predicting Risk of Cardiovascular Disease Events (PREVENT) Risk Scores and Subclinical...

Area of Science:

• Cardiology
• Preventive Medicine
• Public Health

Background:

• The American Heart Association (AHA) Predicting Risk of Cardiovascular Disease Events scores are used to estimate future heart failure (HF) and atherosclerotic cardiovascular disease (ASCVD) events.
• The association between these risk scores and subclinical CVD in asymptomatic populations has not been previously established.

Purpose of the Study:

• To investigate the relationship between AHA 10-year risk scores for HF and ASCVD and the presence of subclinical CVD in an asymptomatic community cohort.
• To determine if higher predicted cardiovascular disease risk is associated with subclinical indicators of HF and coronary artery disease.

Main Methods:

• Analysis of 1138 participants from the Project Baseline Health Study (PBHS) cohort, all free of known CVD.
• Subclinical CVD was defined using echocardiography (left ventricular diastolic dysfunction, hypertrophy, or low ejection fraction) and coronary artery calcium scoring.
• Logistic regression and ROC curve analysis were employed to assess the association between 10-year risk scores and subclinical CVD.

Main Results:

• Subclinical HF, primarily diastolic dysfunction, was identified in 16% of participants, with prevalence increasing significantly with higher HF risk scores.
• Subclinical coronary artery disease (coronary artery calcium >0) was present in 41% of participants, rising sharply with elevated ASCVD risk scores.
• Each unit increase in 10-year HF risk score showed a 2.67-fold increased odds of diastolic dysfunction (AUC 0.81).
• Each unit increase in 10-year ASCVD risk score correlated with a 2.91-fold increased odds of any coronary calcification (AUC 0.80), with stronger associations for higher calcium scores.

Conclusions:

• In an asymptomatic, CVD-free population, higher predicted 10-year risks for HF and ASCVD are significantly associated with the presence of subclinical CVD.
• The AHA Predicting Risk of CVD Events equations demonstrate utility in identifying individuals with underlying subclinical cardiovascular disease, even in the absence of diagnosed conditions.