Abstract 12330: The Degree of Common Carotid Artery Stenosis and the Risk of Cardiovascular Disease Incidence in the Suita Study

Abstract

Introduction: Little is known about whether common carotid artery (CCA) stenosis is associated with the risk of incident cardiovascular diseases (CVD) in a general population. We aimed to examine the impact of CCA stenosis degree on incident CVD in a general population. Methods: We studied 5,133 Japanese men and women (mean age 59.7 years) without CVD whose CCA was measured by carotid ultrasonography on both sides at baseline (April 1994 to March 2005). We confirmed stenosis by color Doppler and calculated the stenosis degree as a percentage of the stenotic area of the lumen in the cross-section perpendicular to the long axis. The Cox proportional hazard model was used to calculate the multivariable-adjusted hazard ratios (HRs) with 95% confidence intervals (CIs) of CVD and its subtypes for people with CCA stenosis ≥50 % and 25-49 % compared to those with CCA stenosis <25 % after adjusting for cardiovascular risk factors. Results: During 63,687 person-years of follow-up, we observed 400 cases of incident CVD (237 strokes and 163 coronary heart diseases [CHDs]). The respective prevalence of 25-49 % and ≥50 % stenosis were 8.2 % and 5.3 % in men and 3.8 % and 1.1 % in women. The CCA stenosis degree was associated with increased risks of incident CVD and CHD, and marginally increased risks of stroke; the multivariable-adjusted HRs for 25-49 % and ≥50 % compared to <25 % stenosis were 1.29 (0.94-1.77) and 1.88 (1.28-2.75) for CVD, 1.88 (1.19-2.97) and 2.37 (1.35-4.13) for CHD, and 0.95 (0.61-1.49) and 1.69 (0.99-2.88) for stroke. The sex-specific HRs of incident CVD for 25-49 % and ≥50 % compared to <25 % stenosis were 1.60 (1.10-2.33) and 1.85 (1.19-2.88) for men, and 0.80 (0.43-1.50) and 2.40 (1.04-5.55) for women. Conclusion: The degree of CCA stenosis was associated with increased risks of incident CVD, CHD, and stroke in the general population. For the first time, CCA stenosis can be used as a predictive tool for the onset of CVD in a general urban population.