Diabetes Care
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

Published online October 12, 2007
Diabetes Care 31:47-49, 2008
DOI: 10.2337/dc07-1335
© 2008 by the American Diabetes Association
This Article
Right arrow Extract Freely available
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
dc07-1335v1
31/1/47    most recent
Right arrow Purchase Article
Right arrow View Shopping Cart
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow Request Permissions
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Chudleigh, R. A.
Right arrow Articles by Owens, D. R.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Chudleigh, R. A.
Right arrow Articles by Owens, D. R.
Social Bookmarking
Add to CiteULike   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?

Clinical Care/Education/Nutrition/Psychosocial Research
Original Research

Influence of Body Weight on the Performance of Glomerular Filtration Rate Estimators in Subjects With Type 2 Diabetes

Richard A. Chudleigh, MRCP1, Gareth Dunseath, MPHIL1, Rajesh Peter, MRCP1, John N. Harvey, MD, FRCP2, Richard L. Ollerton, PHD3, Steve Luzio, MD1 and David R. Owens, MD, FRCP1

1 Diabetes Research Unit, Llandough Hospital, Penarth, Cardiff, U.K
2 Wrexham Maelor Hospital, Wrexham, North Wales, U.K
3 School of Computing and Mathematics, University of Western Sydney, Sydney, Australia

Address correspondence and reprint requests to Richard Chudleigh, 20 Llewelyn Goch, Parc Rhydlafar, St. Fagans, Cardiff, U.K. CF5 6HR. E-mail: rachudleigh{at}hotmail.com

Abbreviations: BSA, body surface area • eGFR, estimated glomerular filtration rate • GFR, glomerular filtration rate • MDRD, Modification of Diet in Renal Disease


   INTRODUCTION
TOP
 INTRODUCTION
RESEARCH DESIGN AND METHODS--
 RESULTS--
 CONCLUSION--
 References
 
The American Diabetes Association recommends estimation of glomerular filtration rate (GFR) (1) by either the Cockcroft-Gault (2) or the Modification of Diet in Renal Disease (MDRD) (3) equation in all patients with diabetes. The implication is that these equations provide similar results. Body weight is a numerator in the Cockcroft-Gault equation; however, it is absent from the MDRD equation. This may explain some of the difference in the ability of these equations to estimate GFR in patients with type 2 diabetes, over 80% of whom are obese (4), and may lead to discrepancies in reporting of chronic kidney disease stage (5). Our study was designed to identify whether body weight may explain variability in performance between the Cockcroft-Gault and MDRD equations in patients newly diagnosed with type 2 diabetes.


   RESEARCH DESIGN AND METHODS—
TOP
 INTRODUCTION
 RESEARCH DESIGN AND METHODS--
RESULTS--
 CONCLUSION--
 References
 
The study population consisted of 293 subjects newly diagnosed with type 2 diabetes; 96% were Caucasian and the remainder of South Asian origin. No African-American subjects were included.

Following an overnight fast, anthropometric and biochemical measurements were made. Subjects were intravenously cannulated, and 1 MBq 51Cr-EDTA was administered at 0 min, with further blood sampling at 44, 120, 180, and 240 min.

The 51Cr-EDTA plasma clearance method for GFR measurement, corrected for body surface area (BSA), has been validated previously (6). This allows estimation of a two-compartment model. A close correlation exists between total plasma clearance of 51Cr-EDTA and inulin clearance determined by the classical technique (7).

Creatinine levels were determined using the OCD (Johnson & Johnson) dry slide system on the Vitros 750 x RC and 950 analyzer. The coefficients of variation were 4.2% at a creatinine concentration of 103 µmol/l and 1.92% at 16 µmol/l.

Estimated GFR (eGFR) (in milliliters per min per 1.73 meters squared) was calculated by the Cockcroft-Gault formula, corrected for BSA (2), and the MDRD formula (3), both of which are shown below:

Cockcroft-Gault formula:

Formula 1(eq. 1)
where k is 1.23 for men and 1.04 for females and c adjusts for BSA. c = 1.73/BSA with BSA calculated using the DuBois formula (8):

Formula 2(eq. 2)

MDRD formula:

Formula 3(eq. 3)

Statistical analysis
To compare formula performance over different body weight ranges while maintaining group sizes suitable to make the calculations, subjects were grouped into tertiles according to body weight. Other comparisons were made using the full ranges of the relevant data. eGFR results derived by the Cockcroft-Gault and MDRD formulae were compared with isotopic GFR by means of two-tailed paired and unpaired t tests as appropriate (confirmed by nonparametric equivalents for abnormal distributions) and {chi}2 test for proportions and linear regression. Statistical test assumptions were checked graphically and by use of suitable statistics as required. All calculations were performed using SPSS (version 12.0.1). Results are presented as mean ± SD unless otherwise indicated. P < 0.05 was taken to indicate statistical significance.


   RESULTS—
TOP
 INTRODUCTION
 RESEARCH DESIGN AND METHODS--
 RESULTS--
CONCLUSION--
 References
 
Demographic characteristics of study participants are summarized in Table 1. Normoalbuminuric subjects comprised 91% of participants. A positive correlation between GFR and body weight (r = 0.194) was found and was also seen across weight groups. Mean fasting plasma glucose and A1C were similar between groups.


View this table:
[in this window]
[in a new window]

  		Table 1— Demographic data and performance of GFR estimation equations

 
Performance of Cockcroft-Gault–and MDRD formulae–derived eGFRs according to body weight is presented in Table 1. Bias values show that eGFR significantly underestimates isotopic GFR. However, the negative bias of the Cockcroft-Gault equation reduced toward zero with increasing body weight, whereas the negative bias of the MDRD equation increased with increasing body weight.

Precision values are similar in all groups. Wide 95% limits of agreement, which range from negative to positive values, were seen for both equations regardless of body weight. Accuracy of the Cockcroft-Gault equation improved with increasing body weight, contrasting with the MDRD equation, with which accuracy declined with increasing weight.


   CONCLUSION—
TOP
 INTRODUCTION
 RESEARCH DESIGN AND METHODS--
 RESULTS--
 CONCLUSION--
References
 
eGFR is used for assessment of kidney function in patients with diabetes. Despite validation in chronic kidney disease (9,10), eGFR has limitations in patients with preserved kidney function (11).

Inclusion of weight in the Cockcroft-Gault equation and its absence from the MDRD equation led us to speculate that this may explain some of the variability in eGFR results. In obese patients with established kidney disease, the Cockcroft-Gault equation overestimates GFR while underestimating GFR in lean subjects; performance of the MDRD equation in such patients was consistent regardless of weight (12).

We found that both formulae introduced significant biases and, in average terms, underestimated GFR. Consistent with previous studies (12,13), bias of the Cockcroft-Gault formula was most pronounced in lean subjects, diminishing with increasing body weight. Conversely, bias of the MDRD equation increased with increasing body weight. Improvement in accuracy of the Cockcroft-Gault equation was seen with increasing weight, while accuracy of the MDRD equation was better in lean subjects.

In obese patients, excess body weight is mainly adipose tissue, whereas creatinine is primarily generated by muscle. In the Cockcroft-Gault equation, body weight is proportional to GFR; therefore, increasing body weight without a proportional increase in creatinine generation will tend to increase the estimation of GFR. This may explain the attenuation in underestimation of GFR seen by the Cockcroft-Gault equation in obese patients. However, weight is not included in the MDRD equation and therefore cannot influence performance.

This study of predominantly male Caucasian subjects with type 2 diabetes and normoalbuminuria found the Cockcroft-Gault equation to be influenced by body weight, whereas the MDRD is to a far lesser degree. This may lead to significant differences in eGFR results.

Although the MDRD equation underestimates GFR, unlike the Cockcroft-Gault equation its performance is not greatly affected by body weight. However, the Cockcroft-Gault equation did provide a more accurate estimation of GFR in obese subjects with newly diagnosed type 2 diabetes, a substantial clinical population.

Currently, improved estimators of GFR for use in patients with diabetes are being developed (14). While we await these improvements, clearly the Cockcroft-Gault and MDRD equations cannot be used interchangeably. A consensus on estimation of GFR in patients with diabetes is required.


   Footnotes
 
Published ahead of print at http://care.diabetesjournals.org on 12 October 2007. DOI: 10.2337/dc07-1335.

A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C Section 1734 solely to indicate this fact.

Received for publication May 22, 2007. Accepted for publication October 1, 2007.


   References
TOP
 INTRODUCTION
 RESEARCH DESIGN AND METHODS--
 RESULTS--
 CONCLUSION--
 References
 

  1. American Diabetes Association: Standards of medical care in diabetes—2007 (Position Statement). Diabetes Care 30 (Suppl. 1):S4–S41, 2007
  2. Cockcroft DW, Gault HM: Prediction of creatinine clearance from serum creatinine. Nephron 16:31–41, 1976[Medline]
  3. Levey AS, Greene T, Kusek J, Beck G: A simplified equation to predict glomerular filtration rate from serum creatinine (Abstract). J Am Soc Nephrol 11:155A, 2000
  4. Pi-Sunyer FX: Weight loss and mortality in type 2 diabetes. Diabetes Care 23:1451–1452, 2000[Medline]
  5. Rodrigo P, Andres M: Cockcroft-Gault or abbreviated-MDRD equations; which ‘weighs' more in cardiovascular risk? Nephrol Dial Transplant 21:2342–2343, 2006[Free Full Text]
  6. Vora JP, Burch A, Owens DR, Peters JP: Simultaneous determination of glomerular filtration rate and effective renal plasma flow. Clin Phys Physiol Meas 12:269–277, 1991[Medline]
  7. Brochner-Mortensen J: Current status on assessment and measurement of glomerular filtration rate. Clinical Physiol 5:1–17, 1985
  8. DuBois D, DuBois EF: A formula to estimate the approximate surface area if height and weight are known. Ann Internal Med 17:863–871, 1916
  9. Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D, the Modification of Diet in Renal Disease Study Group: A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Ann Intern Med 130:461–470, 1999[Abstract/Free Full Text]
  10. Lewis J, Agodoa L, Cheek D, Greene T, Middleton J, O’Connor D, Ojo A, Phillips R, Sika M, Wright J Jr: Comparison of cross-sectional renal function measurements in African Americans with hypertensive nephrosclerosis and of primary formulas to estimate glomerular filtration rate. Am J Kidney Dis 38:744–753, 2001[Medline]
  11. Chudleigh RA, Dunseath G, Evans W, Harvey JN, Evans P, Ollerton R, Owens DR: How reliable is estimation of glomerular filtration rate at diagnosis of type 2 diabetes? Diabetes Care 30:300–305, 2007[Abstract/Free Full Text]
  12. Rigalleau V, Lasseur V, Perlemoine C, Barthe N, Raffaitin C, Chauveau P, Combe C, Gin H: Cockcroft-Gault formula is biased by body weight in diabetic patients with renal impairment. Metab Clin Exp 55:108–112, 2005
  13. Verhave JC, Fesler P, Ribstein J, Cailar G, Mimran A: Estimation of renal function in subjects with normal serum creatinine levels: influence of age and body mass index. Am J Kidney Diseases 46:233–241, 2005[Medline]
  14. Stevens LA, Coresh J, Greene T, Levey A: Assessing kidney function: measured and estimated glomerular filtration rate. N Engl J Med 354:2473–2483, 2006[Free Full Text]

Add to CiteULike CiteULike   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati    What's this?



This Article
Right arrow Extract Freely available
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
dc07-1335v1
31/1/47    most recent
Right arrow Purchase Article
Right arrow View Shopping Cart
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow Request Permissions
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Chudleigh, R. A.
Right arrow Articles by Owens, D. R.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Chudleigh, R. A.
Right arrow Articles by Owens, D. R.
Social Bookmarking
Add to CiteULike   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Diabetes Diabetes Care Clinical Diabetes Diabetes Spectrum