title: New predictive equations improve monitoring of kidney function in patients with diabetes.
abstract: OBJECTIVE
  The Cockcroft-Gault and Modification of Diet in Renal Disease (MDRD) equations poorly predict glomerular filtration rate (GFR) decline in diabetic patients. We sought to discover whether new equations based on serum creatinine (the Mayo Clinic Quadratic [MCQ] or reexpressed MDRD equations) or four cystatin C-based equations (glomerular filtration rate estimated via cystatin formula [Cys-eGFR]) were less biased and better predicted GFR changes.
  
  
  METHODS
  In 124 diabetic patients with a large range of isotopic GFR (iGFR) (56.1 +/- 35.3 ml/min per 1.73 m2 [range 5-164]), we compared the performances of the equations before and after categorization in GFR tertiles. A total of 20 patients had a second determination 2 years later.
  
  
  RESULTS
  The Cockcroft-Gault equation was the least precise. The MDRD equation was the most precise but the most biased according to the Bland-Altman procedure. By contrast with the MDRD and, to a lesser extent, the MCQ, three of the four Cys-eGFRs were not biased. All equations overestimated the low GFRs, whereas only the MDRD and Rule's Cys-eGFR equations underestimated the high GFRs. For the subjects studied twice, iGFR changed by -8.5 +/- 17.9 ml/min per 1.73 m2. GFR changes estimated by the Cockcroft-Gault (-4.5 +/- 6.8) and MDRD (-5.7 +/- 6.2) equations did not correlate with the isotopic changes, whereas new equation-predicted changes did: MCQ: -8.7 +/- 9.4 (r = 0.44, P < 0.05) and all four Cys-eGFRs: -6.2 +/- 7.4 to -7.3 +/- 8.4 (r = 0.60 to 0.62, all P < 0.005), such as 100/cystatin-C (r = 0.61, P < 0.005).
  
  
  CONCLUSIONS
  The new predictive equations better estimate GFR than the Cockcroft-Gault equation. Although the MDRD equation remains the most accurate, it poorly predicts GFR decline, as it overestimates low and underestimates high GFRs. This bias is lesser with the MCQ and Cys-eGFR equations, so they better predict GFR changes.
authors.affiliation: Biochemistry Laboratory, Hôpital Haut-Lévêque, Pessac, France. marie-christine.beauvieux@chu-bordeaux.fr
authors.forename: Marie-Christine
authors.initials: MC
authors.lastname: Beauvieux
authors.forename: Françoise
authors.initials: F
authors.lastname: Le Moigne
authors.forename: Catherine
authors.initials: C
authors.lastname: Lasseur
authors.forename: Christelle
authors.initials: C
authors.lastname: Raffaitin
authors.forename: Caroline
authors.initials: C
authors.lastname: Perlemoine
authors.forename: Nicole
authors.initials: N
authors.lastname: Barthe
authors.forename: Philippe
authors.initials: P
authors.lastname: Chauveau
authors.forename: Christian
authors.initials: C
authors.lastname: Combe
authors.forename: Henri
authors.initials: H
authors.lastname: Gin
authors.forename: Vincent
authors.initials: V
authors.lastname: Rigalleau
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000419:Albuminuria; D003404:Creatinine / Q000097:blood; D055316:Cystatin C; D015891:Cystatins; D003920:Diabetes Mellitus / Q000503:physiopathology*; D003928:Diabetic Nephropathies / Q000503:physiopathology* / Q000517:prevention & control; D004032:Diet; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D007677:Kidney Function Tests; D008297:Male; D008875:Middle Aged; D008991:Monitoring, Physiologic; D011237:Predictive Value of Tests
chemical_list: C525030:CST3 protein, human; D055316:Cystatin C; D015891:Cystatins; D003404:Creatinine