title: Association of chronic kidney disease with the spectrum of ankle brachial index the CHS (Cardiovascular Health Study).
abstract: OBJECTIVE
  This study sought to determine the association of chronic kidney disease (CKD) with high ankle brachial index (ABI) measurement and to compare its strength with that of CKD with a low ABI.
  
  
  BACKGROUND
  CKD is an important risk factor for cardiovascular disease (CVD) events. A high ABI, a marker of lower extremity arterial stiffness, is associated with CVD events and mortality. The association between CKD and high ABI is unknown.
  
  
  METHODS
  The CHS (Cardiovascular Health Study) enrolled community-living people >65 years of age and measured kidney function and ABI. Glomerular filtration rate (GFR) was estimated using equations that incorporated either cystatin C or creatinine, and CKD was defined by estimated GFR <60 ml/min/1.73 m(2). The ABI was categorized as low (<0.90), low-normal (0.90 to 1.09), normal (1.10 to 1.40), and high (>1.40 or incompressible). Multinomial logistic regression was used to evaluate the associations of CKD with ABI categories.
  
  
  RESULTS
  Among 4,513 participants, 23% had CKD, 13% had a low ABI, and 3% had a high ABI. In models adjusted for age, sex, race, hypertension, diabetes, smoking, body mass index, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and C-reactive protein, cystatin C-based CKD was associated with both low ABI (relative risk [RR]: 2.0; 95% confidence interval [CI]: 1.6 to 2.5; p <0.001) and high ABI (RR: 1.6; 95% CI: 1.0 to 2.3; p = 0.03). Results were similar when CKD was defined by creatinine.
  
  
  CONCLUSIONS
  CKD is associated with both the high and the low extremes of ABI in community-living older people. Future studies should evaluate whether arterial stiffness is an important mechanism leading to CVD in people with CKD.
authors.affiliation: Department of Medicine, University of California San Diego, USA. joeix@ucsd.edu
authors.forename: Joachim H
authors.initials: JH
authors.lastname: Ix
authors.forename: Ronit
authors.initials: R
authors.lastname: Katz
authors.forename: Ian H
authors.initials: IH
authors.lastname: De Boer
authors.forename: Brian R
authors.initials: BR
authors.lastname: Kestenbaum
authors.forename: Matthew A
authors.initials: MA
authors.lastname: Allison
authors.forename: David S
authors.initials: DS
authors.lastname: Siscovick
authors.forename: Anne B
authors.initials: AB
authors.lastname: Newman
authors.forename: Mark J
authors.initials: MJ
authors.lastname: Sarnak
authors.forename: Michael G
authors.initials: MG
authors.lastname: Shlipak
authors.forename: Michael H
authors.initials: MH
authors.lastname: Criqui
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D055109:Ankle Brachial Index; D002097:C-Reactive Protein / Q000378:metabolism; D002318:Cardiovascular Diseases / Q000097:blood / Q000209:etiology* / Q000503:physiopathology; D002908:Chronic Disease; D015331:Cohort Studies; D003430:Cross-Sectional Studies; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D007674:Kidney Diseases / Q000097:blood / Q000150:complications* / Q000503:physiopathology*; D008055:Lipids / Q000097:blood; D008297:Male; D012307:Risk Factors
chemical_list: D008055:Lipids; D002097:C-Reactive Protein