ABSTRACT
BACKGROUND: Atherosclerotic renal artery stenosis (RAS) is a frequently overlooked clinical entity that can cause progressive renal failure and uncontrolled hypertension. Revascularization of a stenosed renal artery is associated with improved clinical outcomes including the prevention of renal failure. Thus, it is important to recognize all potential candidates for renal artery revascularization. In a general population referred for diagnostic cardiac catheterization, RAS of any severity was found in 30% of patients and significant stenosis (> or = 50% diameter narrowing) was found in 15% of patients. The number of minority groups is increasing in the US population, and RAS in this population is not well investigated. Our purpose was to determine the prevalence and risk factors associated with RAS in minority patients referred for diagnostic cardiac catheterization. METHODS: Abdominal aortography was performed in 171 consecutive minority patients referred for diagnostic cardiac catheterization (hispanics = 115, African Americans = 56). The association of clinical and angiographic variables with RAS was examined using univariate and multivariate logistic regression analyses. RESULTS: Renal artery stenosis of any severity was identified in 13.5% of patients (unilateral 7.7%, bilateral 5.8%). Significant RAS was found in 7.7% of patients (unilateral 4.8%, bilateral 2.9%). Independent predictors of RAS included age (mean +/-1SD, 68 +/-10 vs 57 +/-12 yr, P < 0.001, for patients with vs without RAS), coronary artery disease, and elevated serum creatinine levels (> 115 micromol/L). Race/ethnicity (hispanics vs African Americans), sex, smoking, congestive heart failure, diabetes mellitus, peripheral vascular disease, and hypertension were not independent predictors. CONCLUSIONS: Renal artery stenosis in minority patients undergoing diagnostic cardiac catheterization is less common than reported in white patients, is similar in hispanics and African Americans, and is similar in women and men. The clinical and angiographic features are helpful in predicting its presence.
