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Systemic Errors in Estimating Renal Function by Cockroft-Gault or MDRD Equations
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Reported by Jules Levin
8th Intl Workshop on Adverse Drug Reactions and Lipodystrophy in HIV
San Francisco, Sept 24-26, 2006
Author: Don Kotler (St Luke's-Roosevelt Hospital Center, NY, NY) et al.
Assessment of renal function is important in clinical medicine when drug safety and efficacy are affected by variations in renal function. Creatinine clearance is the most widely used parameter for evaluating renal function:
-the value is calculated from 24 hour urinary creatinine excretion and serum creatinine concentration.
-Creatinine excretion is related to total muscle mass and muscle protein turnover.
Several prediction equations have been applied clinically, and are based upon age, sex, race, height, weight, and serum creatinine concentration.
The effects of nutritional alterations on renal function have received little attention.
The aim of this study is to determine the influence of malnutrition and obesity on the prediction of creatinine clearance by Cockcroft-Gault (CG) and Model for End Stage Renal Disease MDRD) equations.
The study was prospective cross sectional: studies designed in the pre-HAART
era. Studies performed in 122 subjects without intrinsic renal disease:
- 97 men and 25 women
- 79 HIV+ inpatients or outpatients and 43 healthy controls
- mean age 42 (19-65 yrs)
- mean weight as % of ideal 103 (56-206%)
- mean BMI 23.3 (12.9-40.6 kgm3)
CrCl by 24 hr urine collection.
CrCl estimated using the CG & MDRD equations:
- for MDRD, the data were adjusted to estimated total body fat surface area by Mosteller's formula, rather than normalized to 1.73 m2.
Body cell mass by bioelectrical impedance analysis (BIA).
RESULTS
CrCl 24 was significantly associated with estimates of body cell mass (r2=0.26, p<0.001), but was not associated with BMI (r2=0.02, p=0.1).
CrCl 24 was significantly associated with MDRD or CG estimates, using either actual or ideal body weight (r2 range 0.31-0.35, p<0.001), while CG and MDRD estimates correlated closely with each other (r2=0.78, p<0.001).
The prediction errors by CG & MDRD were directly related to the magnitude of CrCl 24, with overestimation at low values and underestimation at high values (r2 range 0.34-0.38, p<0.001).
The prediction error for CrCl by CG was related to BMI (p=0.001), and the prediction errors for CrCl by CG & MDRD were related to body cell mass, (p=0.002) and p<0.001, respectively), with overestimation at low values and underestimation at high values.
DISCUSSION
CrCl is affected by nutritional status, specifically body cell mass, of which skeletal muscle is the largest compenent.
Estimations of CrCl using height, weight, serum creatinine concentration, and demographics alone contain sestematic errors related to nutritional status:
- CrCl is overestimated in malnourished and underestimated in obese subjects, with potential effects on drug safety and efficacy.
- The error could be due to variations in the relationship between weight & muscle mass. (note from Jules Levin: so body builders can be affected).
Conclusion/hypothesis
Substitution of a measure of muscle mass instead of body weight may provide a less biased measure of CrCl in malnourished or obese subjects.
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