Modification of Diet in Renal Disease versus Chronic Kidney Disease Epidemiology Collaboration equation to estimate glomerular filtration rate in obese patients
Nephrol Dial Transplant (2013) 28 (Suppl. 4): iv122–iv130
doi: 10.1093/ndt/gft329
Advance Access publication 11 September 2013
Original Articles
Modification of Diet in Renal Disease versus Chronic Kidney
Disease Epidemiology Collaboration equation to estimate
glomerular filtration rate in obese patients
Antoine Bouquegneau1,
3
François Vrtovsnik ,
4
Etienne Cavalier ,
Marcelle Rorive5,
1
Jean-Marie Krzesinski ,
Pierre Delanaye1
and Martin Flamant2
Correspondence and offprint requests to: Pierre
Delanaye; E-mail:
A B S T R AC T
Background. Obesity is a recognized risk factor for both the development and progression of chronic kidney disease (CKD).
Accurate estimation of glomerular filtration rate (GFR) is thus
important in these patients. We tested the performances of two
creatinine-based GFR estimates, the Modification of Diet in
Renal Disease (MDRD) and the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations, in an obese population.
Methods. Patients with body mass index (BMI) > 30 kg/m2
were included. The reference method for measured GFR
(mGFR) was 51Cr-EDTA (single-injection method, two blood
samples at 120 and 240 min). Both indexed and non-indexed
results were considered. Serum creatinine was measured using
the IDMS-traceable compensated Jaffe method. Mean bias
(eGFR–mGFR), precision (SD around the bias) and accuracy
within 30% (percentage of estimations within 30% of mGFR)
were calculated for both equations.
Results. The population included 366 patients (185 women)
from two different areas. Mean age was 55 ± 14 years, and
© The Author 2013. Published by Oxford University Press on
behalf of ERA-EDTA. All rights reserved.
Department of Nephrology-Dialysis-Transplantation, University of
Liège, CHU Sart Tilman, Liège, Belgium,
2
Department of Renal Physiology, Hôpital Bichat, AP-HP and Denis
Diderot University, Paris, France,
3
Department of Nephrology, Hôpital Bichat, AP-HP and Denis
Diderot University, Paris, France,
4
Department of Clinical Chemistry, University of Liège, CHU Sart
Tilman, Liège, Belgium and
5
Department of Diabetology, University of Liège, CHU Sart Tilman,
Liège, Belgium
Keywords: CKD-EPI, creatinine, glomerular filtration rate,
MDRD, obesity
mean BMI was 36 ± 7 kg/m2. Mean mGFR was 56 ± 26 mL/
min/1.73 m2 (71 ± 35 mL/min without indexation). In the
total population, mean bias was +1.9 ± 14.3 and +4.6 ± 14.7
mL/min/1.73 m2 (P < 0.05), and accuracy 30% was 80 and
76% for the MDRD and CKD-EPI equations (P < 0.05),
respectively. In patients with mGFR > 60 mL/min/1.73 m2,
mean bias was +4.6 ± 18.4 and +9.3 ± 17.2 mL/min/1.73 m2
(P < 0.05), and accuracy 30% was 81 and 79% (NS) for the
MDRD and CKD-EPI equations, respectively.
Conclusions. The CKD-EPI equation did not outperform the
MDRD study equation in this population of obese patients.
INTRODUCTION
Obesity has become one of the most important public health
problems worldwide [1–4]. High body mass index (BMI) is
known to accelerate the progression of renal dysfunction in
chronic kidney disease (CKD) patients [5–8]. Several epidemiological studies reported that increased BMI was associated
with an increased risk of end-stage renal disease (ESRD)
iv122
Emmanuelle Vidal-Petiot2,
1
Patients were recruited from two university hospital centres
(CHU Sart Tilman, Liège, Belgium and Bichat Hospital, Paris,
France). Eligible patients were >18 years and had a BMI > 30
kg/m2. Patients treated with steroids, cimetidine or trimethoprim were excluded. In the non-CKD obese population, indication for GFR measurement was before a potential living
kidney donation or before a slimming diet. In CKD obese
patients, GFR was measured in the context of CKD follow-up,
and not because of obesity.
GFR was measured by plasma clearance of 51Cr-EDTA:
single-injection method with two samples at 120 and 240 min
and Bröchner–Mortensen correction [33, 34]. BSA was calculated with the equation developed by Gehan and George [35].
Indexed GFR values were only slightly modified, and therefore
results of our study did not change (data not shown) if other
BSA calculation formulas (Dubois [36], Haycock [37] and
Mosteller [38] equations) were used.
Serum creatinine was sampled the same day as GFR
determination and measured using the IDMS-traceable
MDRD eGFR ¼ 175 ðSCreatÞ1:154 ðageÞ0:203
ð0.742 if patient is femaleÞ;
CKD-EPI eGFR = 141 minðSCreat/k, 1Þa
maxðSCreat/k, 1Þ1:209
0.993age 1.018 ½if female;
where SCreat is serum creatinine in mg/dL, age is in years, κ is
0.7 for females, 0.9 for males, α is −0.329 for females and
−0.411 for males, min indicates the minimum of SCreat/κ or 1
and max indicates the maximum of SCreat/κ or 1.
The performances of GFR estimates were assessed with the
following parameters:
Bias expressed the systematic deviation from the mGFR
and was calculated as the mean difference between eGFR and
mGFR.
Relative bias (or % bias) was calculated as absolute bias as a
fraction of mGFR and expressed in percentages.
Precision of the estimates was determined as SD of the
mean difference between eGFR and mGFR.
Accuracy was calculated as the percentage of eGFR values
within 30% of mGFR.
Comparison of bias, precision and accuracy was performed
using t-test, F-test and McNemar paired test, respectively.
We have also considered the performances of the two
equations according to different subgroups (CKD stages) [26].
The definition of the subgroups was set according to mGFR
values.
The correlation between GFR estimated by the different
equations and mGFR was done with the Pearson’s analysis.
The performances of GFR estimated were also evaluated with
the Bland and Altman graphic representation. Sensitivity of
eGFR to detect mGFR below 60 mL/min/1.73 m2 and between
30 and 59 mL/min/1.73 m2 was calculated.
The impact of BMI on the bias of each equation was evaluated with a two-way ANOVA test.
R E S U LT S
Three hundred and sixty-six patients were included in the
study: 181 males and 185 women. Mean age was 55 ± 14 years
and mean BMI was 36 ± 7 kg/m2. Clinical and biological
characteristics of the population are shown in Table 1.
Mean indexed mGFR was 56 ± 26 mL/min/1.73 m2, and
207 subjects (57%) had an mGFR below 60 mL/min/1.73 m2.
When non-indexed GFR was considered, mean mGFR was
71 ± 35 mL/min and 156 patients (43%) were under 60 mL/min.
Indexation modified the CKD stage classification in 14% of
the patients.
In the total population (Table 2), mean bias and precision
were +1.9 ± 14.3 and +4.6 ± 14.7 mL/min/1.73 m2 for the
MDRD study and CKD-EPI equations, respectively (P < 0.05).
iv123
Estimating GFR in obese subjects
ORIGINAL ARTICLE
M AT E R I A L S A N D M E T H O D S
compensated Jaffe method [39]. eGFR was calculated with the
CKD-EPI [25] and MDRD [40] study equations as follows:
defined as the need for kidney transplant or dialysis [9–12].
Obesity-related CKD includes various different pathophysiological factors like glomerular hyperfiltration, intraglomerular
hypert (...truncated)
