Abstract P2010: Extra-Coronary Calcification and Risk of Incident Cardiovascular Disease in Adults 75 and Older: The Atherosclerosis Risk in Communities (ARIC) Study
Abstract
Background: The coronary artery calcium (CAC) score is one of the most potent predictors of cardiovascular disease (CVD). During a CAC scan, extra-coronary calcification (ECC) can be simultaneously measured, but the independent prognostic value is unknown in adults aged 75 and older. Methods: We studied 1,831 ARIC participants at visit 7 (mean age 80.4 [SD 4.2] years, 62% female, 20% black) without prevalent CVD. We quantified ECC (Agatston score) at five specific sites: aortic valve calcification (AVC), aortic valve ring calcification (AVR), mitral valve calcification (MVC), ascending aorta calcification (ASA), and descending aorta calcification (DSA). We ran multivariable Cox models with total CVD events (composite of adjudicated myocardial infarction, stroke, and heart failure) as the outcome. Results: Over a mean follow-up of 2.6 years, 113 incident CVD events occurred. The prevalence of ECC>0 varied by site: AVC (45%), ARC (86%), MVC (47%), ASA (25%), and DSA (89%). After adjusting for traditional CVD risk factors (Model 1 in Table), prevalence of each ECC was associated with incident CVD events (e.g., hazard ratio 1.30, [95%CI 1.09-1.56] for AVC). However, after further adjustment for the CAC score (Model 2 in Table), only AVC remained significant (hazard ratio 1.22 [1.02-1.47]). When adding each ECC into the base model with traditional risk factors and CAC score, AVC, but not other ECCs, significantly improved CVD risk prediction (Δc-statistic 0.014 [95%CI 0.001 to 0.033] from c-statistic of 0.703 to 0.718). Conclusion: Of ECCs measured, AVC was particularly robustly associated with incident CVD and improved CVD prediction beyond CAC score in the 75-and-older population. Our findings suggest the value of quantifying ECC when CAC scan was performed in this population.
Article Details
Authors (8)
Siyu Zou
College of Chemical Engineering
Hairong Liu
Yejin Mok
Johns Hopkins University, Baltimore, Maryland, United States
Abhishek Gami
The Johns Hopkins University, Baltimore, Maryland, United States
Lin Yee Chen
Matthew Budoff
The Lundquist Institute, Torrance, California, United States
Michael Blaha
JOHNS HOPKINS HOSPITAL, Baltimore, Maryland, United States
Kunihiro Matsushita
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (K.M.).