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CP-075 MDRD and CKD-EPI equations versus Cockroft-Gaultin in dose optimisation
  1. L Gratacós1,
  2. D Soy2,
  3. A Botey3
  1. 1Hospital Universitario de Girona Dr Josep Trueta, Pharmacy, Girona, Spain
  2. 2Hospital Clínic de Barcelona, Pharmacy, Barcelona, Spain
  3. 3Hospital Clínic de Barcelona, Nephrology, Barcelona, Spain

Abstract

Background The Cockroft-Gault (CG) equation has been commonly used to estimate glomerular filtration rate (GFR) and optimise the dose of medicines. Currently, many laboratories have incorporated the Modification of Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations into their analytical results as a surrogate for renal function.

Purpose To assess whether the CKD-EPI and MDRD formulae (four variables) correlate well with CG for estimating GFR.

Materials and methods Retrospective observational study in adult hospitalised patients included in a pharmacokinetic vancomycin monitoring programme from November 2011 to November 2012. Patients with a baseline serum creatinine (SCr) greater than 2 mg/dL, body mass index lower than 18.5 kg/m2 or greater than 40 kg/m2, or treated with an extracorporeal depuration technique were excluded. Baseline SCr, lean body weight and body surface area were measured and used to calculate GFR by CG (CrClCG). These values were compared to those obtained from the CKD-EPI and MDRD formulae. Intraclass correlation coefficients (ICC) were estimated to evaluate the concordance between CrClCG and CKD-EPI and MDRD. Bland-Altman plots, bias and precision were calculated to contrast all creatinine clearance estimates.

Results 166 patients (59.6% male) were recruited. Their median age was 65 years; (interquartile rate: 52–76). ICC obtained from comparing MDRD and CKD-EPI values against CrClCG were 0.907 (IC95:0.693–0.958) and 0.903 (IC95:0.867–0.929) respectively. Both equations have a very good concordance with CG. CKD-EPI shows a statistically significant better mean bias (0.069 vs. 0.152; p < 0.0001) and precision (0.177 vs. 0.194; p = 0.0477) than MDRD. Both equations slightly overestimate CrClCG. Bland-Alman plot limits of agreement were 50.3;-22.3 for MDRD graphs and 41;-33.6 for CKD-EPI.

Conclusions In the population studied, both formulae (MDRD and CKD-EPI) correlate well with CG but CKD-EPI showed better bias and precision. Although either formula may be used instead of CG, CKD-EPI would be a better choice.

No conflict of interest.

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