title: Cystatin C and estimates of renal function: searching for a better measure of kidney function in diabetic patients.
abstract: BACKGROUND
  Early identification of impairment in renal function is crucial in diabetic patients. Serum cystatin C may be the most sensitive indicator of glomerular filtration rate (GFR) in the clinical setting.
  
  
  METHODS
  We compared cystatin C with creatinine, the Cockcroft-Gault (C-G) formula, and the Modification of Diet in Renal Disease (MDRD) study equation for the assessment of early decreased renal function in 288 diabetic patients (125 type 1, 163 type 2) with renal impairment [GFR: 4-222 mL x min(-1) x (1.73 m(2))(-1)]. Relationships of cystatin C, creatinine, and iohexol clearance were linearized by plotting their reciprocals in a simple regression model. Diagnostic efficiency was calculated from ROC curves.
  
  
  RESULTS
  In this study population, cystatin C (P = 0.0013) was better correlated with GFR (r = 0.857) than were creatinine (r = 0.772), C-G (r = 0.750), and MDRD (r = 0.806), a result replicated in patients with normal renal function (P = 0.023, type 1; P = 0.011, type 2), but not in those with decreased GFR. Mean cystatin C concentrations showed step-by-step statistically significant increases as GFR decreased, allowing very early detection of reduction in renal function. At 90 mL x min(-1) x (1.73 m(2))(-1) and 75 mL x min(-1) x (1.73 m(2))(-1) cut-points, diagnostic efficiencies of cystatin C (89% and 92%) were better than those of the other variables (79%-82% and 85%-86%, respectively; P = 0.01).
  
  
  CONCLUSIONS
  All data supported the value of serum cystatin C compared with conventional estimates based on serum creatinine measurement for detecting very early reduction of renal function. Use of cystatin C to measure renal function will optimize early detection, prevention, and treatment strategies for diabetic nephropathy.
authors.affiliation: Dipartimento di Endocrinologia e Metabolismo, Azienda Ospedaliero Universitaria di Pisa, Pisa, Italy. plaura@immr.med.unipi.it
authors.forename: Laura
authors.initials: L
authors.lastname: Pucci
authors.forename: Stefano
authors.initials: S
authors.lastname: Triscornia
authors.forename: Daniela
authors.initials: D
authors.lastname: Lucchesi
authors.forename: Carmen
authors.initials: C
authors.lastname: Fotino
authors.forename: Giovanni
authors.initials: G
authors.lastname: Pellegrini
authors.forename: Ennia
authors.initials: E
authors.lastname: Pardini
authors.forename: Roberto
authors.initials: R
authors.lastname: Miccoli
authors.forename: Stefano
authors.initials: S
authors.lastname: Del Prato
authors.forename: Giuseppe
authors.initials: G
authors.lastname: Penno
mesh_terms: D000328:Adult; D003287:Contrast Media; D003404:Creatinine / Q000097:blood; D055316:Cystatin C; D015891:Cystatins / Q000097:blood*; D003922:Diabetes Mellitus, Type 1 / Q000503:physiopathology*; D003924:Diabetes Mellitus, Type 2 / Q000503:physiopathology*; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D007472:Iohexol / Q000493:pharmacokinetics; D007668:Kidney / Q000503:physiopathology*; D008297:Male; D008875:Middle Aged; D012372:ROC Curve; D012044:Regression Analysis
chemical_list: C525030:CST3 protein, human; D003287:Contrast Media; D055316:Cystatin C; D015891:Cystatins; D007472:Iohexol; D003404:Creatinine