Ability of retinopathy to predict cardiovascular disease in patients with type 2 diabetes mellitus

Am J Cardiol. 2009 May 15;103(10):1364-7. doi: 10.1016/j.amjcard.2009.01.345. Epub 2009 Apr 1.


It is important identify patients with very high cardiovascular risk to intensify their therapy. Our aim was to assess the association between retinopathy and incident cardiovascular events (cardiovascular disease [CVD]) in patients with type 2 diabetes mellitus (DM). Patients were included if they had type 2 DM and a visible fundus. Baseline clinical and biochemical variables, including urinary albumin excretion rate, were collected. Clinical end points were nonfatal or fatal cardiovascular events (unstable angina including revascularization, nonfatal or fatal myocardial infarction, transient ischemic attack, nonfatal or fatal stroke, lower-leg amputation, terminal chronic heart failure, sudden death). Cox multivariate regression models were used to evaluate the risk associated with each variable and the independent contribution of baseline retinopathy. A total of 458 patients were included, with mean follow-up time of 6.7 +/- 2.6 years. Incident CVD rates were 30.7 per 1,000 patient-years in patients with a normal fundus, 56.7 in patients with nonproliferative retinopathy, and 90.7 in patients with proliferative retinopathy (p <0.0001). In multivariate analysis, nonproliferative retinopathy (hazard ratio 1.71, 95% confidence interval 1.1 to 2.66, p = 0.017) and proliferative retinopathy (hazard ratio 2, 95% confidence interval 1.1 to 3.56, p = 0.019) were significantly associated with incident CVD. In conclusion, retinopathy proved to be an independent risk marker for CVD in patients with type 2 DM.

MeSH terms

  • Aged
  • Biomarkers / analysis
  • Cardiovascular Diseases / complications*
  • Cardiovascular Diseases / epidemiology*
  • Diabetes Mellitus, Type 2 / complications*
  • Diabetic Retinopathy / complications*
  • Female
  • Follow-Up Studies
  • Humans
  • Incidence
  • Male
  • Middle Aged
  • Myocardial Infarction
  • Proportional Hazards Models
  • Risk Factors


  • Biomarkers