The predictive value of different equations for estimation of glomerular filtration rate in patients with coronary artery disease — Results from the AtheroGene study☆

2016 
Abstract Background Impaired renal function leads to dramatically increased risk for the development and progression of coronary artery disease (CAD). Therefore we aimed to assess the predictive value of different equations for estimated glomerular filtration rate (eGFR) in CAD-patients. Methods From the AtheroGene study 2135 patients were included. eGFR was calculated using the 4-variable Modification of Diet in Renal Disease (4MDRD) equation for serum creatinine (sCr), the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation for sCr and cystatin C (CysC) each alone, and in combination (CysC/sCr). eGFR was assessed regarding the combined outcome of cardiovascular death and non-fatal myocardial infarction and regarding complex CAD represented by a SYNTAX score ≥23. Median follow-up was 4.3years. Results Only the CKD-EPI equation using CysC could differentiate between eGFR >90ml/min/1.73m 2 vs. eGFR 60–90ml/min/1.73m 2 according to the occurrence of an endpoint event (log-rank test p=0.009). In the Cox regression analysis only eGFR calculated by CKD-EPI equation for CysC (Hazard ratio per 1 standard deviation (HR) 1.27 (95% CI 1.07–1.50); p=0.007) and for CysC/sCr (HR 1.22 (95% CI 1.02–1.46); p=0.026) were predictive regarding the outcome after adjustment for cardiovascular risk factors and Nt-proBNP. Furthermore, only eGFR calculated by CKD-EPI equation for CysC (odds ratio (OR) 1.57 (95% CI 1.36–1.78); p Conclusion In patients with CAD the CKD-EPI equation for CysC and for CysC/sCr provided the best predictive value regarding the prognosis and the severity of CAD.
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