title: Does cystatin C improve the precision of Cockcroft and Gault's creatinine clearance estimation?
abstract: BACKGROUND
  Cystatin C is increasingly used to estimate renal function, but its large intraindividual variability limits its practical value. This study aimed at verifying whether the clinical practice of associating cystatin C determination with serum creatinine (Cr) improved the ability of the Cockcroft and Gault formula to estimate creatinine clearance (CrCl).
  
  
  METHODS
  It was an observational cross-sectional study of 134 in-patients with mildly impaired renal function. Using the Hoek et al formula (glomerular filtration rate (GFR)/1.73m2 = - 4.32 + 80.35/cystatin C mg/L), multivariate linear regressions (LREG) and artificial neural networks (ANN), we integrated cystatin C in the Cockcroft and Gault formula and analyzed the potential superiority of this procedure by comparing its performance with that of the two algorithms taken separately.
  
  
  RESULTS
  The inclusion of cystatin C in the Cockcroft and Gault formula using the data of an LREG (CrCl = 0.371 x (Hoek et al) + 0.589 x Cockcroft and Gault), a simple mean between the two algorithms or ANN ameliorated the CrCl estimation precision allowing an absolute error reduction of approximately 4, 4 and 6%, respectively (relative values 12, 12 and 17%).
  
  
  CONCLUSIONS
  Although the combination of the Hoek et al and Cockcroft and Gault formulae using both linear and non-linear mathematical methods allowed a statistically significant reduction in the estimation error generated by Cockcroft and Gault, considering the small impact on the estimation precision and the large intraindividual variation of both cystatin C and Cr, this procedure probably has no clinical relevance.
authors.affiliation: Division of Nephrology, Department of Internal Medicine, Carità Hospital, Locarno, Switzerland. luca.gabutti@eoc.ch
authors.forename: Luca
authors.initials: L
authors.lastname: Gabutti
authors.forename: Nicola
authors.initials: N
authors.lastname: Ferrari
authors.forename: Giorgio
authors.initials: G
authors.lastname: Mombelli
authors.forename: Claudio
authors.initials: C
authors.lastname: Marone
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D003404:Creatinine / Q000097:blood* / Q000652:urine*; D003430:Cross-Sectional Studies; D055316:Cystatin C; D015891:Cystatins / Q000097:blood*; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D007674:Kidney Diseases / Q000097:blood / Q000175:diagnosis* / Q000652:urine; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D015203:Reproducibility of Results
chemical_list: C525030:CST3 protein, human; D055316:Cystatin C; D015891:Cystatins; D003404:Creatinine