Relationship of gender, age, and body mass index to errors in predicted kidney function

Background. Previous studies have shown conflicting data on accuracy of equations for kidney function prediction. The present work analysed the relationship of gender, age and body mass index (BMI) to error of predictions by the Cockcroft–Gault equation (CGeq), the simplified equation of the Modification of Renal Diseases Study (MDRDeq) and the Mayo Clinic equation (Mayoeq). Methods. Inulin clearance (glomerular filtration rate; GFR) and other variables were measured in 380 subjects of both sexes, aged 18–88 years, with and without kidney disease. GFR was defined as low when <60 ml/min x 1.73 m2. BMI was used for definition of underweight/overweight. Relative error of predictions was used as an index of bias. It was calculated as prediction minus GFR (positive values =overestimates, negative values = underestimates) and expressed as a percentage of the GFR. Absolute error was used as an index of imprecision and was calculated as the absolute value of relative error. Results. CGeq relative error was inversely associated with age and directly associated with BMI (P<0.001), but not with gender or GFR. MDRDeq relative error was inversely associated with female gender and GFR (P<0.001), but not with age or BMI. Mayoeq relative error was directly associated with male gender, BMI and GFR (P<0.01), but not with age. Absolute error was higher for CGeq than for MDRDeq but only at low GFR (P<0.001). Mayoeq had a higher absolute error than CGeq and MDRDeq (P<0.01). Conclusions. Errors of predictions varied not only with GFR but also with gender, age and BMI. Without using creatinine assay calibration, Mayoeq was less accurate than both MDRDeq and CGeq, whereas MDRDeq was slightly more precise than CGeq but only at low GFR