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Erschienen in:
01.01.2011 | Article
Estimated glomerular filtration rate and albuminuria are independent predictors of cardiovascular events and death in type 2 diabetes mellitus: the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) study
Erschienen in: Diabetologia | Ausgabe 1/2011
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Aims/hypothesis
We investigated effects of renal function and albuminuria on cardiovascular outcomes in 9,795 low-risk patients with diabetes in the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) study.
Methods
Baseline and year 2 renal status were examined in relation to clinical and biochemical characteristics. Outcomes included total cardiovascular disease (CVD), cardiac and non-cardiac death over 5 years.
Results
Lower estimated GFR (eGFR) vs eGFR ≥90 ml min−1 1.73 m−2 was a risk factor for total CVD events: (HR [95% CI] 1.14 [1.01–1.29] for eGFR 60–89 ml min−1 1.73 m−2; 1.59 [1.28–1.98] for eGFR 30–59 ml min−1 1.73 m−2; p < 0.001; adjusted for other characteristics). Albuminuria increased CVD risk, with microalbuminuria and macroalbuminuria increasing total CVD (HR 1.25 [1.01–1.54] and 1.19 [0.76–1.85], respectively; p = 0.001 for trend) when eGFR ≥90 ml min−1 1.73 m−2. CVD risk was further modified by renal status changes over the first 2 years. In multivariable analysis, 77% of the effect of eGFR and 81% of the effect of albumin:creatinine ratio were accounted for by other variables, principally low HDL-cholesterol and elevated blood pressure.
Conclusions/interpretation
Reduced eGFR and albuminuria are independent risk factors for cardiovascular events and mortality rates in a low-risk population of mainly European ancestry. While their independent contributions to CVD risk appear small when other risk factors are considered, they remain excellent surrogate markers in clinical practice because they capture risk related to a number of other characteristics. Therefore, both should be considered when assessing prognosis and treatment strategies in patients with diabetes, and both should be included in risk models.