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Published on: August 28, 2018
Longitudinal Changes in Coronary Artery Calcium Distribution and Atherosclerotic Cardiovascular Disease Risk
Shyon Parsa1,2, Colby R Ayers1, Ayeeshik Kole1
1Division of Cardiology, Department of Internal Medicine University of Texas Southwestern Medical Center Dallas TX.
Insights
The coronary artery calcium (CAC) diffusivity index (DI) helps predict coronary heart disease (CHD) events in younger adults. Higher CAC DI at baseline improves risk models, but changes over time offer less predictive value.
Area of Science:
- Cardiology
- Preventive Medicine
- Medical Imaging
Background:
- The Agatston score measures coronary artery calcium (CAC) but lacks spatial distribution data.
- The CAC diffusivity index (DI) may enhance cardiovascular risk stratification for individuals with CAC > 0.
- This study investigated if CAC distribution refines cardiovascular event prediction beyond the Agatston score in a young cohort.
Purpose of the Study:
- To assess the predictive value of CAC spatial distribution using the CAC DI.
- To determine if CAC DI improves cardiovascular risk stratification in a young, asymptomatic cohort.
- To compare the prognostic performance of CAC DI against the traditional Agatston score.
Main Methods:
- 1013 participants from the Dallas Heart Study 2 (DHS2) with CAC > 0 and no prior cardiovascular disease were analyzed.
- CAC DI was calculated as 1-(CAC in most affected vessel/total CAC) and categorized (concentrated, standard, diffuse).
- Cox proportional hazards models and C-statistics were used to assess coronary heart disease (CHD), atherosclerotic cardiovascular disease (ASCVD), and mortality risk, adjusting for Agatston CAC, demographics, and traditional risk factors.
Main Results:
- Compared to a concentrated CAC pattern, standard and diffuse patterns were linked to higher incident CHD risk (HR 5.97 and 5.48, respectively; P<0.05).
- While baseline CAC DI contributed to adjusted models for CHD, its predictive impact on atherosclerotic cardiovascular disease (ASCVD) and mortality was less clear.
- Changes in CAC DI over time showed an association with increased CHD and ASCVD risk in partially adjusted models, but this effect was attenuated in fully adjusted models.
Conclusions:
- A higher baseline CAC DI significantly contributes to adjusted models for predicting incident CHD in a young, population-based cohort.
- The spatial distribution of CAC, as measured by DI, offers incremental prognostic information for CHD.
- Temporal changes in CAC DI provided limited additional benefit for cardiovascular event prediction in this cohort.
Background:
The Agatston score quantifies coronary artery calcium (CAC) burden but does not account for its spatial distribution. The CAC diffusivity index (DI) may refine cardiovascular risk stratification in individuals with Agatston CAC>0. This study assessed whether CAC distribution improves cardiovascular event prediction beyond the Agatston score in a young cohort.
Methods:
Among DHS2 (Dallas Heart Study 2) participants with CAC>0 and no prior cardiovascular disease (35% of the cohort), we studied 1013 participants with CAC DI. CAC DI was calculated as 1-(CAC in most affected vessel/total CAC) and categorized as concentrated (<25th percentile), standard (25th-75th percentile), and diffuse (>75th percentile). Cox proportional hazards models and C-statistics assessed coronary heart disease (CHD), atherosclerotic cardiovascular disease, and mortality, adjusting for Agatston CAC, demographics, and traditional risk factors.
Results:
Mean±SD age was 55±9.4 years (49% women, and 47% Black), with a median follow-up of 9±2.5 years (57 CHD and 92 atherosclerotic cardiovascular disease events). Compared with a concentrated CAC pattern, standard and diffuse patterns were associated with incident CHD (hazard ratio, 5.97 [95% CI, 1.24-28.78] and 5.48 [95% CI, 1.04-29.04], respectively; P<0.05) but not atherosclerotic cardiovascular disease in fully adjusted models. Positive and negative changes in CAC DI were associated with increased CHD and atherosclerotic cardiovascular disease risk in models adjusted for pooled cohort equation variables, although effects were attenuated in fully adjusted models. Adding continuous CAC DI did not significantly improve model performance.
Conclusions:
Higher CAC DI at baseline significantly contributes to adjusted models for incident CHD in a young population-based cohort, but temporal changes provided little additional benefit.
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