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Bilateral common carotid artery ultrasound for prediction of incident strokes using intima-media thickness and external diameter: an observational study

Cardiovascular ultrasound(2013)

Cited 17|Views16
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Abstract
Background External common carotid artery (CCA) diameter and intima-media thickness (IMT) are independently associated with incident stroke and other cardiovascular events. Arterial geometry such as large IMT and large diameter may reflect vulnerable plaques and so impact stroke risk. Finally, arterial changes that exist bilaterally may increase stroke risk. Method We studied middle-aged men and women (n=7276) from a prospective observational study who had right (R) and left (L) CCA IMT and external diameters measured via B-mode ultrasound (1987–89) in order to categorize CCA geometry. Using side- and gender-specific IMT and diameter medians, we categorized each measurement as large (≥ median) vs. not large (< median) and defined four geometries: both IMT and diameter were large, only one parameter was large, or neither was large (reference group). Participants were followed for first time stroke through December 31, 1999. We used proportional hazards models to assess associations between right and left CCA geometries with new stroke. We also calculated positive and negative likelihood ratios (+LR and -LR) for CCA bilateral phenotypes as a measure of diagnostic accuracy. Results Presence of both large CCA IMT and large diameter on one side was associated with strong stroke risk even after risk factor adjustment (men: RCCA hazard ratio [HR]=3.7 95% confidence interval [CI]=1.9-7.4; LCCA HR=2.4 95% CI=1.4-4.4; women: RCCA HR=4.0 95% CI=1.5-10.5; LCCA HR=5.7 95% CI=1.7-19.0). Presence of both large IMT and large diameter bilaterally was the strongest predictor of stroke identifying 64% of women and 44% of men who developed strokes. This phenotype showed potential for predicting stroke among individuals (women: +LR=3.1, 95% CI=2.6-3.8; men: +LR=2.3, 95% CI=1.8-2.8). Conclusion Bilateral carotid artery geometries may be useful for stroke risk prediction.
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Key words
stroke,angiology,cardiology,incidence,risk factors,ultrasound
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