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Clin Exp Nephrol. 2012 Jun;16(3):456-63. doi: 10.1007/s10157-011-0583-1. Epub 2012 Jan 26.

Serum cystatin C as a predictor for cardiovascular events in end-stage renal disease patients at the initiation of dialysis.

Author information

1
Division of Nephrology, Department of Internal Medicine, Pusan National University Hospital School of Medicine, Busan, Republic of Korea.

Abstract

BACKGROUND:

There has been no study to investigate whether cystatin C could predict cardiovascular events in incident dialysis patients. We aimed to delineate the role of serum cystatin C and cystatin C-based estimated glomerular filtration rate (eGFR(cysC)) for prediction of cardiovascular events.

METHODS:

This study included 66 end-stage renal disease patients who survived for >3 months after the start of dialysis, and serum cystain C levels were measured at the point of dialysis initiation.

RESULTS:

Serum cystatin C was correlated with blood urea nitrogen (r = 0.537, p < 0.001), serum creatinine (r = 0.480, p < 0.001) and smoking (r = 0.284, p = 0.021). Cystatin C was inversely correlated with age (r = -0.316, p = 0.01) and eGFR(Cr) by modification of diet in renal disease (r = -0.533, p < 0.001). Kaplan-Meier analysis for cardiovascular events revealed that patients in the group with lower cystatin C levels (<4.14 mg/L) had a better event-free survival rate than patients in the group with higher cystatin C levels (≥4.14 mg/L) (p = 0.039). In univariate analysis, cystatin C (hazard ratio (HR) 2.62, p = 0.011) and eGFR(cysC) (HR 0.64, p = 0.004) were significant factors for the prediction of cardiovascular events. After multivariate adjustment, serum cystatin C and eGFR(cysC) were independent determinants of cardiovascular events (HR 3.952, p = 0.001 and HR 0.640, p = 0.004, respectively).

CONCLUSION:

Serum cystatin C might be an independent marker of cardiovascular events in incident dialysis patients. Furthermore, eGFR(cysC) based on measured serum cystatin C could have a new role in predicting cardiovascular events beyond the estimation of true GFR.

PMID:
22278599
DOI:
10.1007/s10157-011-0583-1
[Indexed for MEDLINE]

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