title: Non-diabetic chronic kidney disease influences retinal microvasculature.
abstract: BACKGROUND
  Chronic kidney disease (CKD) is characterized by increased cerebrovascular risk. Retinal vessel analysis (RVA) is an accepted measure of the retinal microvasculature, mirrors hypertension and cardiovascular morbidity. Epidemiological studies demonstrate narrower retinal arterioles with declining renal function. The effect of CKD on the retinal microcirculation remains uncertain.
  
  
  METHODS
  RVA was performed in 34 non-diabetic CKD patients and 33 age-matched volunteers with normal renal function. Retinal photographs were digitized, vascular lumen diameters measured and the ratio of retinal arteriolar and venular lumen diameters (AVR) calculated. Office blood pressure (BP) was measured and cardiovascular risk factors assessed.
  
  
  RESULTS
  AVR was lower in CKD patients as compared to age-matched volunteers (0.77 +/- 0.05 vs. 0.86 +/- 0.06; p < 0.05). In particular, retinal arterioles were narrower in CKD patients as compared to volunteers (169.6 +/- 20.4 vs. 189.5 +/- 14.2 microm; p < 0.01). In CKD, estimated glomerular filtration rate, BP and renin-angiotensin system blocker independently predicted AVR. Moreover, retinal arteriolar diameter independently predicted renal function (beta = 0.33; p < 0.05).
  
  
  CONCLUSIONS
  CKD narrowed retinal arterioles suggesting an extended effect of CKD on the cerebral microvasculature. This study shows that in CKD patients, renal function, BP status and renin-angiotensin system blockade independently predict AVR as a marker for microvascular damage and that retinal microvasculature can predict renal function.
authors.affiliation: Department of Nephrology, Klinikum rechts der Isar, Technical University Munich, Munich, Germany. marcus.baumann@lrz.tum.de
authors.forename: Marcus
authors.initials: M
authors.lastname: Baumann
authors.forename: Sonja
authors.initials: S
authors.lastname: Schwarz
authors.forename: Konstantin
authors.initials: K
authors.lastname: Kotliar
authors.forename: Maximilian
authors.initials: M
authors.lastname: von Eynatten
authors.forename: Arno Schmidt
authors.initials: AS
authors.lastname: Trucksaess
authors.forename: Klaus
authors.initials: K
authors.lastname: Burkhardt
authors.forename: Jens
authors.initials: J
authors.lastname: Lutz
authors.forename: Uwe
authors.initials: U
authors.lastname: Heemann
authors.forename: Ines
authors.initials: I
authors.lastname: Lanzl
mesh_terms: D000368:Aged; D000886:Anthropometry; D001794:Blood Pressure / Q000502:physiology; D015992:Body Mass Index; D002196:Capillaries / Q000473:pathology; D002784:Cholesterol / Q000097:blood; D002908:Chronic Disease; D003430:Cross-Sectional Studies; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D007668:Kidney / Q000502:physiology / Q000503:physiopathology; D007674:Kidney Diseases / Q000473:pathology*; D008297:Male; D008875:Middle Aged; D012044:Regression Analysis; D012084:Renin-Angiotensin System / Q000502:physiology; D012171:Retinal Vessels / Q000473:pathology*
chemical_list: D002784:Cholesterol