title: Frequency and predictors of renal artery stenosis in patients with coronary artery disease.
abstract: BACKGROUND
  Renal artery stenosis (RAS) remains underdiagnosed because of nonspecific clinical manifestations, including in patients with coronary artery disease (CAD).
  
  
  OBJECTIVE
  To estimate the prevalence and identify predictors of RAS in patients with CAD undergoing coronary angiography.
  
  
  METHODS
  University-based medical centre.
  
  
  METHODS
  We enrolled 650 consecutive patients (mean age=67+/-10 years, 80% men) with confirmed CAD. All patients underwent selective renal arteriography in the same procedure. We estimated the prevalence of RAS, defined as a >50% lesion. Multiple variable analysis of factors associated with presence of RAS was carried out using a logistic regression model. Variables that emerged as predictors by single-variable analysis were included in the model, along with variables that were tentatively associated with RAS, based on a literature review.
  
  
  RESULTS
  RAS was detected in 94 patients (14.5%, 95% CI: 11.8-17.2%), including 20 (3.1%) with bilateral lesions. By single-variable analysis and presence and number of coronary artery stenoses (P<.001), hypertension (P=.001), and creatinine clearance <90 ml/min (P<.001) were associated with an increased risk of RAS. By multiple variable analysis, male sex (P<.05), presence and number of coronary artery lesions (P<.01), hypertension (P=.001), and renal insufficiency (P<.001) predicted the presence of RAS.
  
  
  CONCLUSIONS
  The main clinical predictors of RAS in patients with CAD were hypertension, renal insufficiency, and multivessel CAD. These observations might help defining a high-risk subgroup of patients in need of meticulous investigations of both CAD and RAS.
authors.affiliation: INSERM, U642, Rennes, F-35000, France. romain.ollivier@chu-rennes.fr
authors.forename: Romain
authors.initials: R
authors.lastname: Ollivier
authors.forename: Dominique
authors.initials: D
authors.lastname: Boulmier
authors.forename: David
authors.initials: D
authors.lastname: Veillard
authors.forename: Guillaume
authors.initials: G
authors.lastname: Leurent
authors.forename: Stéphane
authors.initials: S
authors.lastname: Mock
authors.forename: Marc
authors.initials: M
authors.lastname: Bedossa
authors.forename: Hervé
authors.initials: H
authors.lastname: Le Breton
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D017023:Coronary Angiography; D023921:Coronary Stenosis / Q000150:complications / Q000000981:diagnostic imaging* / Q000453:epidemiology; D003404:Creatinine / Q000097:blood; D005260:Female; D006801:Humans; D006973:Hypertension / Q000150:complications; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015995:Prevalence; D011446:Prospective Studies; D012078:Renal Artery Obstruction / Q000000981:diagnostic imaging* / Q000453:epidemiology / Q000209:etiology; D051437:Renal Insufficiency / Q000150:complications; D018570:Risk Assessment; D012307:Risk Factors; D012720:Severity of Illness Index; D012737:Sex Factors
chemical_list: D003404:Creatinine