Evaluation of creatinine-based and cystatin C-based equations for estimation of glomerular filtration rate in type 1 diabetic patients

Arch. endocrinol. metab. (Online); 60 (2), 2016
Publication year: 2016

ABSTRACT Objective Several formulas based in different biomarkers may be used to estimate glomerular filtration rate (GRF). However, all of them have some limitations, and it is very important to evaluate their performances in different groups of patients. Therefore, we compared GFR, as estimated by creatinine-based and cystatin C-based equations, according to albuminuria, in type 1 diabetes (T1DM), in an observational case-control study.

Subjects and methods T1DM patients were classified according to albuminuria:

normoalbuminuric (n = 63), microalbuminuric (n = 30), macroalbuminuric (n = 32). GFR was calculated using creatinine-based and cystatin C-based (aMDRD, CKD-EPIcr, CKD-EPIcys, MacIsaac, Tan and CKD-EPIcrcys) equations. Spearman Correlation was used to evaluate the correlation of GFR estimated by the formulas with albuminuria. ROC curves were constructed to compare AUCs of GFR estimated by equations, in reference to macroalbuminuria. Sensibility, specificity and accuracy were calculated for a cut-off < 60 mL/min/1.73 m2. Results GFR estimated by creatinine-based and cystatin C-based equations significantly differed among normoalbuminuric, microalbuminuric and macroalbuminuric patients. Spearman correlation and AUCs of GFR estimated by creatinine-based and cystatin C-based formulas were very similar to each other, though cystatin C-based equations presented better correlation with albuminuria and higher AUCs than the creatinine-based ones, and the best accuracy to detect macroalbuminuric patients. Conclusion Although GFR estimated by all creatinine-based and cystatin C-based equations permitted the differentiation between T1DM patients, according to albuminuria, cystatin C-based equations presented best accuracy to detect macroalbuminuria in T1DM patients and should be considered in the clinical routine in order to increase the possibility of early diagnostic of chronic renal disease.

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