scholarly journals Cystatin C and Cardiovascular Risk

2009 ◽  
Vol 55 (11) ◽  
pp. 1932-1943 ◽  
Author(s):  
Nevio Taglieri ◽  
Wolfgang Koenig ◽  
Juan Carlos Kaski

Abstract Background: Patients with chronic kidney disease (CKD) are at high risk for developing cardiovascular disease (CVD) and cardiovascular events. Cystatin C, a protease inhibitor synthesized in all nucleated cells, has been proposed as a replacement for serum creatinine for the assessment of renal function, particularly to detect small reductions in glomerular filtration rate. Content: This report presents a review of the role of cystatin C as a predictor of cardiovascular risk. Summary: Patients with higher circulating cystatin C concentrations appear to have an increased cardiovascular risk profile, i.e., they are older and have a higher prevalence of systemic hypertension, dyslipidemia, documented CVD, increased body mass index, and increased concentrations of C-reactive protein. Prospective studies have shown, in various clinical scenarios, that patients with increased cystatin C are at a higher risk of developing both CVD and CKD. Importantly, cystatin C appears to be a useful marker for identifying individuals at a higher risk for cardiovascular events among patients belonging to a relatively low-risk category as assessed by both creatinine and estimated glomerular filtration rate values. Of interest, elastolytic proteases and their inhibitors, in particular cystatin C, have been shown to be directly involved in the atherosclerotic process. Increased concentrations of cystatin C appear to be indicative of preclinical kidney disease associated with adverse outcomes. Clinical studies involving direct glomerular filtration rate measurements are required to ascertain both the true role of this promising marker in renal disease and whether atherogenic factors like inflammation can account for increases in cystatin C concentrations, thus explaining its predictive value in CVD.

2015 ◽  
Vol 61 (10) ◽  
pp. 1265-1272 ◽  
Author(s):  
Jeffrey W Meeusen ◽  
Andrew D Rule ◽  
Nikolay Voskoboev ◽  
Nikola A Baumann ◽  
John C Lieske

Abstract BACKGROUND The Kidney Disease Improving Global Outcomes (KDIGO) guideline recommends use of a cystatin C–based estimated glomerular filtration rate (eGFR) to confirm creatinine-based eGFR between 45 and 59 mL · min−1 · (1.73 m2)−1. Prior studies have demonstrated that comorbidities such as solid-organ transplant strongly influence the relationship between measured GFR, creatinine, and cystatin C. Our objective was to evaluate the performance of cystatin C–based eGFR equations compared with creatinine-based eGFR and measured GFR across different clinical presentations. METHODS We compared the performance of the CKD-EPI 2009 creatinine-based estimated GFR equation (eGFRCr) and the newer CKD-EPI 2012 cystatin C–based equations (eGFRCys and eGFRCr-Cys) with measured GFR (iothalamate renal clearance) across defined patient populations. Patients (n = 1652) were categorized as transplant recipients (n = 568 kidney; n = 319 other organ), known chronic kidney disease (CKD) patients (n = 618), or potential kidney donors (n = 147). RESULTS eGFRCr-Cys showed the most consistent performance across different clinical populations. Among potential kidney donors without CKD [stage 2 or higher; eGFR >60 mL · min−1 · (1.73 m2)−1], eGFRCys and eGFRCr-Cys demonstrated significantly less bias than eGFRCr; however, all 3 equations substantially underestimated GFR when eGFR was <60 mL · min−1 · (1.73 m2)−1. Among transplant recipients with CKD stage 3B or greater [eGFR <45 mL · min−1 · (1.73 m2)−1], eGFRCys was significantly more biased than eGFRCr. No clear differences in eGFR bias between equations were observed among known CKD patients regardless of eGFR range or in any patient group with a GFR between 45 and 59 mL · min−1 · (1.73 m2)−1. CONCLUSIONS The performance of eGFR equations depends on patient characteristics that are readily apparent on presentation. Among the 3 CKD-EPI equations, eGFRCr-Cys performed most consistently across the studied patient populations.


2016 ◽  
Vol 1 ◽  
pp. 55-67 ◽  
Author(s):  
Lisandro D. Colantonio ◽  
Rikki M. Tanner ◽  
David G. Warnock ◽  
Orlando M. Gutiérrez ◽  
Suzanne Judd ◽  
...  

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