Predictors of renal artery stenosis in patients undergoing cardiac catheterization for suspected coronary artery disease

AimThis study determined the prevalence of Renal Artery Stenosis (RAS) and established its predictors in patients undergoing cardiac catheterization for suspected Coronary Artery Disease (CAD).Methods1266 patients underwent coronary angiogram for suspected CAD. Following coronary angiogram, bilateral selective renal angiogram was performed. Study population was split into cohorts with and without RAS. A binary logistic regression model was used to identify univariate predictors of RAS. Significant univariate predictors were used to build a multivariate logistic regression model. Comparative accuracy of various models in predicting RAS was estimated by computing areas under the Receiver Operating Characteristic (ROC) curve.ResultsPrevalence of significant RAS in study population was 6.0%. In univariate analysis, mean age (p = 0.002), diabetes mellitus (p = 0.009), hypertension of more than five years duration (p = 0.034), serum creatinine concentration of >1 mg per 100 ml (p = 0.009), peripheral arterial disease (p = 0.019), and significant CAD (p = 0.037) were predictors of RAS. In the multivariate analysis, serum creatinine concentration (p = 0.002), peripheral arterial disease (p = 0.017), Two-vessel CAD (p = 0.043), and Three-vessel CAD (p = 0.007) were independent predictors of RAS. Areas under the non-crossing ROC curves revealed that a simple model incorporating two-vessel CAD and three-vessel CAD had an acceptable accuracy in predicting RAS.ConclusionIt may not be appropriate to extrapolate the findings of research conducted in other demographic settings to Indian patients. “Drive by” renal angiogram in Indian settings may be done only in patients with multi-vessel CAD presenting with indisputable clinical indications. However, in the long run, we should be open to new research.