Evaluation of Carotid Artery Atherosclerosis and Arterial Stiffness in Cardiovascular Disease Risk: An Ongoing Prospective Study From the Kailuan Cohort

Abstract

Objective: To assess whether carotid artery ultrasonography and brachial-ankle pulse wave velocity (baPWV) measurement can accurately predict cardiovascular and cerebrovascular events, and all-cause mortality in patients with cardiovascular diseases (CVD). Methods: Patients from the Kailuan Study Stroke Cohort (Tangshan, China) who underwent carotid artery ultrasonography and baPWV measurement between June 2010 and June 2011 were included in this study. The effects of carotid plaque, baPWV, and their combination on cardiovascular events, including myocardial infarction (MI), cerebral ischemic stroke, cerebrovascular events, and all-cause mortality, were evaluated using Kaplan-Meier analysis and Cox proportional hazards regression. Results: A total of 4,899 participants (59.7% males; 54.18 ± 11.52 years old) were analyzed. During a mean follow-up of 5.68 ± 0.66 years, the incidence of cardiovascular events and all-cause mortality were 4.94‰ person-years and 7.02‰ person-years, respectively; 32.8% of participants had both carotid artery atherosclerosis and increased arterial stiffness. A high baPWV alone was associated with an increased risk of CVD events [hazard ratio (HR): 2.68; 95% confidence interval (95% CI): 1.20–6.00; P = 0.007] and cerebral infarction (HR: 5.92; 95% CI: 1.76–19.93; P = 0.004), but not with MI or all-cause death. The presence of both carotid plaque and high baPWV was highly associated with an increased risk of CVD events (HR: 4.65; 95% CI: 2.06–10.45; P < 0.001) and cerebral infarction (HR: 9.21; 95% CI: 2.71–31.19; P < 0.001), but not with MI or all-cause death. Similar results were obtained by the Kaplan-Meier analyses. Conclusion: The presence of carotid plaque and high baPWV were associated with a high risk of CVD events and ischemic stroke. Moreover, the combination of carotid artery ultrasonography and baPWV measurement could predict the risk for CVD ability more accurately than a single measurement alone.