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Published on: December 2, 2016
The 2013 ACC/AHA risk score and subclinical cardiac remodeling and dysfunction: Complementary in cardiovascular
Nicholas Cauwenberghs1, Kristofer Hedman2, Yukari Kobayashi3
1Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Sciences, University of Leuven, Belgium.
Insights
Echocardiography improves cardiovascular risk assessment beyond traditional scores for atherosclerotic cardiovascular disease (ASCVD). Adding echocardiographic data significantly enhances prediction of adverse cardiovascular events in intermediate-to-high risk individuals.
Area of Science:
- Cardiology
- Preventive Medicine
- Medical Imaging
Background:
- Cardiovascular (CV) risk stratification tools for atherosclerotic CV diseases (ASCVD) may be enhanced by echocardiography.
- The study investigates the complementary role of ASCVD risk scores and echocardiography in predicting adverse CV outcomes within a community setting.
Purpose of the Study:
- To evaluate if echocardiographic profiling improves cardiovascular risk stratification beyond established ASCVD risk scores.
- To determine the added value of echocardiography in predicting adverse CV events in conjunction with traditional risk factors.
Main Methods:
- 984 community-dwelling adults (40-79 years) underwent CV risk profiling and echocardiography.
- 10-year ASCVD risk was calculated using Pooled Cohort Equations; participants were stratified into low, borderline, or intermediate-to-high risk categories.
- Cardiovascular events were tracked for an average of 7.5 years.
Main Results:
- Cardiac remodeling and/or dysfunction probability increased with higher ASCVD risk.
- Individuals with intermediate-to-high ASCVD risk and at least one left ventricular (LV) abnormality had a significantly higher risk of CV events (HR: 3.00).
- Incorporating LV abnormalities into ASCVD risk models significantly improved predictive capabilities (C-statistics, integrated discrimination, and net reclassification).
Conclusions:
- Echocardiographic profiling enhances CV risk stratification, particularly for individuals at intermediate-to-high ASCVD risk.
- Echocardiography can supplement traditional ASCVD risk grading for more accurate CV disease prediction.
Background:
Echocardiography might enhance cardiovascular (CV) risk stratification beyond tools grading the risk for atherosclerotic CV diseases (ASCVD). We therefore studied the complementarity between the ASCVD risk score recommended by American cardiology societies and echocardiographic profiling in predicting adverse CV outcome in the community.
Methods:
984 community-dwelling individuals between 40 and 79 years old (51.3% women) underwent CV risk profiling and echocardiography. We estimated their 10-year ASCVD risk from baseline risk factors using the Pooled Cohort Equations. Participants were categorized as at low (<2.5%), borderline (2.5-<7.5%) or intermediate-to-high (≥7.5%) ASCVD risk. Main outcome was the incidence of CV events collected on average 7.5 years later.
Results:
The probability for cardiac remodeling and/or dysfunction as assessed by echocardiography rose progressively with increasing 10-year ASCVD risk. During follow-up, 116 participants experienced at least one CV endpoint (15.8 events per 1000 person-years). With increasing 10-year ASCVD risk, the CV event rate increased stronger in participants with ≥1 LV abnormality at baseline. Indeed, in individuals with an intermediate-to-high ASCVD risk and ≥1 LV abnormality at baseline, the risk was significantly higher than the average population risk for a first CV event (HR: 3.00, P < 0.001). Adding the presence of ≥1 LV abnormality to a ASCVD risk score-based model yielded significant improvement in C-statistics (P = 0.024), integrated discrimination (P = 0.0085) and net reclassification (P < 0.001) for adverse CV events.
Conclusions:
Echocardiographic profiling enhanced CV risk stratification in individuals at intermediate-to-high ASCVD risk. Echocardiographic screening might supplement traditional ASCVD risk grading for CV disease prediction.
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