Cerebral microvascular disease predicts renal failure in type 2 diabetes

J Am Soc Nephrol. 2010 Mar;21(3):520-6. doi: 10.1681/ASN.2009050558. Epub 2010 Jan 28.

Abstract

Abnormalities in small renal vessels may increase the risk of developing impaired renal function, but methods to assess these vessels are extremely limited. We hypothesized that the presence of small vessel disease in the brain, which manifests as silent cerebral infarction (SCI), may predict the progression of kidney disease in patients with type 2 diabetes. We recruited 608 patients with type 2 diabetes without apparent cerebrovascular or cardiovascular disease or overt nephropathy and followed them for a mean of 7.5 years. At baseline, 177 of 608 patients had SCI, diagnosed by cerebral magnetic resonance imaging. The risk for the primary outcome of ESRD or death was significantly higher for patients with SCI than for patients without SCI [hazard ratio, 2.44; 95% confidence interval (CI) 1.36 to 4.38]. The risk for the secondary renal end point of any dialysis or doubling of the serum creatinine concentration was also significantly higher for patients with SCI (hazard ratio, 4.79; 95% CI 2.72 to 8.46). The estimated GFR declined more in patients with SCI than in those without SCI; however, the presence of SCI did not increase the risk for progression of albuminuria. In conclusion, independent of microalbuminuria, cerebral microvascular disease predicted renal morbidity among patients with type 2 diabetes.

MeSH terms

  • Aged
  • Albuminuria / epidemiology
  • Cerebrovascular Circulation
  • Cerebrovascular Disorders / epidemiology*
  • Cerebrovascular Disorders / pathology
  • Diabetes Mellitus, Type 2 / epidemiology*
  • Diabetes Mellitus, Type 2 / pathology
  • Diabetic Nephropathies / epidemiology*
  • Female
  • Follow-Up Studies
  • Glomerular Filtration Rate
  • Humans
  • Incidence
  • Kaplan-Meier Estimate
  • Kidney Failure, Chronic / epidemiology*
  • Magnetic Resonance Angiography
  • Male
  • Microvessels / pathology
  • Middle Aged
  • Morbidity
  • Predictive Value of Tests
  • Proportional Hazards Models
  • Risk Factors