ORCP-375; No. of Pages 6
ARTICLE IN PRESS
Obesity Research & Clinical Practice (2014) xxx, xxx.e1—xxx.e6
ORIGINAL ARTICLE
Estimating glomerular filtration rate in obese subjects Minh T. Nguyen a,∗, Julia Fong b, Shahid Ullah c, Alex Lovell a, Campbell H. Thompson a a
School of Medicine, University of Adelaide, North Terrace, 5000 Adelaide, Australia Royal Adelaide Hospital, North Terrace, 5000 Adelaide, Australia c Flinders Centre for Epidemiology and Biostatistics, School of Medicine, Flinders University, Flinders Dr, Bedford Park, 5042 Adelaide, Australia b
Received 18 November 2013 ; received in revised form 1 April 2014; accepted 20 April 2014
KEYWORDS Overweight; Renal function; GFR; Cockcroft—Gault equation; Lean body mass
∗
Summary The glomerular filtration rate (GFR) can be estimated by an equation that incorporates patients’ age, gender, creatinine and weight or, ideally, lean body mass (LBM). However, measuring LBM is not easy if the patient is obese. The aim was to determine an acceptable bedside method for GFR estimation in obese patients. In 82 obese Caucasian outpatients, anthropometric and other characteristics were collected including LBM by impedance analysis. Estimates of GFR were compared with a reference equation (CCGLBM) using Bland—Altman plots, correlation analysis and an independent sample t-test. The patients (72% female) were aged 43.1 ± 12.7 years with BMI 47.0 ± 8.0 kg/m2 , height 168.4 ± 9.4 cm and serum creatinine 70.3 ± 25.7 M. The GFR estimated by the CCGLBM equation was 98.2 ± 33.6 ml/min compared to other equations which ranged from 100.0 ± 22.8 to 218.4 ± 85.5 ml/min. Any equation incorporating actual body weight overestimated the GFR by >120 ml/min (p < 0.001) with a significant fixed proportional bias (p < 0.001). For GFRs between 20 and 180 ml/min, an equation using ideal body weight (CCGIBW) equated to the CCGLBM estimate. The Modified Diet in Renal Disease and Chronic Kidney Disease Epidemiology Collaboration equations performed as well as the CCGLBM in estimating GFR but with proportional bias (p < 0.001). Considering the ease of calculation of the CCGIBW at the bedside, it has a role in GFR estimation of obese inpatients. © 2014 Asian Oceanian Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.
Corresponding author. Tel.: +61 421815845; fax: +61 8 82224179. E-mail address: [email protected] (M.T. Nguyen).
http://dx.doi.org/10.1016/j.orcp.2014.04.001 1871-403X/© 2014 Asian Oceanian Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.
Please cite this article in press as: Nguyen MT, et al. Estimating glomerular filtration rate in obese subjects. Obes Res Clin Pract (2014), http://dx.doi.org/10.1016/j.orcp.2014.04.001
ORCP-375; No. of Pages 6
ARTICLE IN PRESS
xxx.e2
Introduction Accurate and convenient methods of assessing renal function are important to the practising clinician There is a rising prevalence of obesity in the community [1—3] and obese populations carry increased risk of developing acute kidney failure and chronic kidney disease (CKD) [4—8]. Those drugs which are excreted by the kidneys often need dosage adjustment in conditions where renal function is compromised [1]. making it all the more important that clinicians accurately estimate the renal function of their obese patients. Renal function is usually quantified by the glomerular filtration rate (GFR), the flow rate of filtered fluid through the kidney. The GFR measures the renal clearance of a substance from the plasma and is expressed as the volume of plasma that is completely cleared of that substance per minute. Hence, the ideal filtration marker, whether exogenous or endogenous, is in the plasma at a constant concentration and is cleared only by glomerular filtration, i.e. no non-renal elimination of the substance. Accurate measurement of GFR is methodologically difficult in vivo so surrogate estimates such as creatinine clearance rate and prediction formulae are more commonly used in routine clinical practice. Various equations have been derived to estimate GFR in non-obese populations but there are discrepancies between different methods. The Cockcroft—Gault (CCG) formula adjusted for lean body mass (CCGLBM) is believed superior to these other equations for accurately estimating GFR in obese patients when compared to the gold standard GFR estimation method of radioisotope measurements to determine creatinine clearance [4—10]. However measuring lean body mass (LBM) can be problematic in the obese and requires other equipment such as bioelectrical impedance analysis, a technique not likely available in an Emergency Department or general hospital ward. The question arises — what other estimate of GFR is easily generated at the bedside and also approximates the CCGLBM formula for estimating GFR in the obese over a wide range of renal function? This study aimed to determine an estimate that is suitable for the obese which can be generated more easily than the CCGLBM.
M.T. Nguyen et al. Comprehensive Metabolic Care Clinic at the Royal Adelaide Hospital. Only those with a pacemaker and those weighing over 200 kg were excluded from this study. There were 29% with diabetes mellitus and 50% with hypertension, and 28% were on angiotensin converting enzyme inhibitors or angiotensin 2 receptor blockers. Subjects were unlikely to yet have started a significant dietary treatment such as high protein meal or weight loss because all measurements were taken at patients’ first visit to the clinic. No patient was studied after gastric surgery. Anthropometric, clinical and biological characteristics were recorded for each patient. Weight measurements including LBM were obtained using an electronic scale (Tanita InnerScan, Tanita corp., Tokyo, Japan). The Tanita InnerScan is a single frequency bioelectrical impedance analysis device that uses a tetrapolar footpad-style electrode arrangement and has a capacity of 200 kg. In accordance with the manufacturer’s instructions, the subjects stood on the metal footpads in bare feet, and measurements were determined using predication equations supplied by the manufacturer. All methods of assessing body composition in this patient group are difficult. This method was chosen for feasibility and patient acceptability without significant compromise in accuracy [11,12]. These data were used to estimate each patient’s GFR according to a series of formulae described in Table 1. The value for GFR derived from each formula was plotted against the same patient’s GFR estimated by the CCGLBM equation using a Bland—Altman (BA) analysis. The means of the GFR estimates by the two different equations were compared as was the difference between the two estimates over the observed range of renal function. Fixed and proportional biases were assessed by t-test and regressions analysis. Data are presented as means ± standard deviation unless otherwise stated. Statistical comparisons were made using correlation analysis and independent sample t-tests. A p value less than 0.05 was used to define the level of statistical significance. Approval for this study was obtained from the Royal Adelaide Hospital Research Ethics Committee.
Results Methods Eighty-two obese Caucasian patients were prospectively recruited sequentially from the
Anthropometric, clinical and biological characteristics of the population are shown in Table 2. The BA analysis results are shown in Fig. 1. All equations except for the CCGIBW showed a significant
Please cite this article in press as: Nguyen MT, et al. Estimating glomerular filtration rate in obese subjects. Obes Res Clin Pract (2014), http://dx.doi.org/10.1016/j.orcp.2014.04.001
GFR estimation equations. Numeric Expression
Cockcroft—Gault formula adjusted for lean body mass (CCGLBM) [13] Cockcroft—Gault formula (CCG) [14]
(140−Age (year))×LBM (kg)×Gender Value Gender 72 Serum creatinine(umol/L)
Cockcroft—Gault formula adjusted for ideal body weight (CCGIBW) Cockcroft—Gault formula adjusted for body surface area (CCGBSA) [8]
(140−Age(years))×IBW (kg)×Gender Value Gender Serum Creatinine (umol/L)
Modified Diet in Renal Disease formula (MDRD) [15]
value is 0.85 if female and 1 if male.
(140−Age(years))×Actual Weight(kg)×Gender Value Gender Serum Creatinine(umol/L)
value is 0.85 if female and 1 if male.
value is 0.85 if female and 1 if male.
× measured using the Du Bois formula (140−Age(years))×Actual Weight(kg)×Gender Value Serum Creatinine(umol/L)
ARTICLE IN PRESS
Name of equation
1.73 Gender BSA
value is 0.85 if female and 1 if male. BSA in m2
32, 788 × Serum Creatinine (umol/L)−1.154 × Age(years)−0.203 × Constant1 × Constant2Constant1 is 0.742 if female and 1 if male. Constant2 is 1.212 if black. (146−Age)×[(0.287×Weight)+(9.74×Height2 )] 60×Serum creatinine (mg/dL)
Salazar and Corcoran formulas (SaC) [16]
(137−Age(years))×[(0.285×Weight (kg))+(12.1×Height(m)2 )] 51×Serum Creatinine (mg/dL)
Chronic Kidney Disease Epidemiology Collaboration formula (CKD-EPI) [17]
(mg/dL)) (mg/dL)) 141 × min (Serum creatinine , 1 × max (Serum Creatinine ,1 × 0.993Age(years) ‘‘k’’ is 0.7 for k k females and 0.9 for males. ‘‘a’’ is −0.329 for males and −0.411 for males.
Mayo Quadratic [18]
exp 1.911 +
a
5.249 Serum creatinine(mg/dL)
−
×
2.114 (Serum creatinine (mg/dL))2
ORCP-375; No. of Pages 6
Estimating GFR in obese subjects
−1.209
− 0.00686 × Age(years) − Constant Constant is
0.205 if female and 0 if male.
xxx.e3
Please cite this article in press as: Nguyen MT, et al. Estimating glomerular filtration rate in obese subjects. Obes Res Clin Pract (2014), http://dx.doi.org/10.1016/j.orcp.2014.04.001
Table 1
ORCP-375; No. of Pages 6
ARTICLE IN PRESS
xxx.e4 Table 2
M.T. Nguyen et al. Anthropometrical and biological characteristics of the obese population (N = 82).
Characteristics
Mean
SD
Range
Fixed p value
Proportional p value
Age (years) Weight (kg) Height (cm) Gender (Female %) BMI (kg/m2 ) LBM (kg) BSA (m2 ) Serum creatinine (mol) CCGLBM (ml/min) CCG (ml/min) CCGIBW* (ml/min) CCGBSA (ml/min/1.73 m2 ) MDRD (ml/min/1.73 m2 ) SaC (ml/min) CKDEPI (ml/min/1.73 m2 ) Mayo Quadratic (ml/min)
43.1 132.1 168.4 72.0 47.0 60.0 2.3 70.3 98.2 218.4 100.5 159.0 101.9 162.1 100.0 113.5
12.7 26.9 9.4 — 8.0 11.5 0.3 25.7 33.6 85.5 32.8 52.1 29.6 55.7 22.8 13.2
20.0—76.0 80.3—197.8 147.0—192.0 — 30.4—39.8 40.3—94.6 1.7—3.0 41.0—226.0 20.9—214.8 44.2—461.3 24.2—186.2 33.3—317.5 20.4—178.8 35.9—311.1 19.8—140.8 87.4—152.2
— — — — — — — — —
ARTICLE IN PRESS
Obesity Research & Clinical Practice (2014) xxx, xxx.e1—xxx.e6
ORIGINAL ARTICLE
Estimating glomerular filtration rate in obese subjects Minh T. Nguyen a,∗, Julia Fong b, Shahid Ullah c, Alex Lovell a, Campbell H. Thompson a a
School of Medicine, University of Adelaide, North Terrace, 5000 Adelaide, Australia Royal Adelaide Hospital, North Terrace, 5000 Adelaide, Australia c Flinders Centre for Epidemiology and Biostatistics, School of Medicine, Flinders University, Flinders Dr, Bedford Park, 5042 Adelaide, Australia b
Received 18 November 2013 ; received in revised form 1 April 2014; accepted 20 April 2014
KEYWORDS Overweight; Renal function; GFR; Cockcroft—Gault equation; Lean body mass
∗
Summary The glomerular filtration rate (GFR) can be estimated by an equation that incorporates patients’ age, gender, creatinine and weight or, ideally, lean body mass (LBM). However, measuring LBM is not easy if the patient is obese. The aim was to determine an acceptable bedside method for GFR estimation in obese patients. In 82 obese Caucasian outpatients, anthropometric and other characteristics were collected including LBM by impedance analysis. Estimates of GFR were compared with a reference equation (CCGLBM) using Bland—Altman plots, correlation analysis and an independent sample t-test. The patients (72% female) were aged 43.1 ± 12.7 years with BMI 47.0 ± 8.0 kg/m2 , height 168.4 ± 9.4 cm and serum creatinine 70.3 ± 25.7 M. The GFR estimated by the CCGLBM equation was 98.2 ± 33.6 ml/min compared to other equations which ranged from 100.0 ± 22.8 to 218.4 ± 85.5 ml/min. Any equation incorporating actual body weight overestimated the GFR by >120 ml/min (p < 0.001) with a significant fixed proportional bias (p < 0.001). For GFRs between 20 and 180 ml/min, an equation using ideal body weight (CCGIBW) equated to the CCGLBM estimate. The Modified Diet in Renal Disease and Chronic Kidney Disease Epidemiology Collaboration equations performed as well as the CCGLBM in estimating GFR but with proportional bias (p < 0.001). Considering the ease of calculation of the CCGIBW at the bedside, it has a role in GFR estimation of obese inpatients. © 2014 Asian Oceanian Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.
Corresponding author. Tel.: +61 421815845; fax: +61 8 82224179. E-mail address: [email protected] (M.T. Nguyen).
http://dx.doi.org/10.1016/j.orcp.2014.04.001 1871-403X/© 2014 Asian Oceanian Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.
Please cite this article in press as: Nguyen MT, et al. Estimating glomerular filtration rate in obese subjects. Obes Res Clin Pract (2014), http://dx.doi.org/10.1016/j.orcp.2014.04.001
ORCP-375; No. of Pages 6
ARTICLE IN PRESS
xxx.e2
Introduction Accurate and convenient methods of assessing renal function are important to the practising clinician There is a rising prevalence of obesity in the community [1—3] and obese populations carry increased risk of developing acute kidney failure and chronic kidney disease (CKD) [4—8]. Those drugs which are excreted by the kidneys often need dosage adjustment in conditions where renal function is compromised [1]. making it all the more important that clinicians accurately estimate the renal function of their obese patients. Renal function is usually quantified by the glomerular filtration rate (GFR), the flow rate of filtered fluid through the kidney. The GFR measures the renal clearance of a substance from the plasma and is expressed as the volume of plasma that is completely cleared of that substance per minute. Hence, the ideal filtration marker, whether exogenous or endogenous, is in the plasma at a constant concentration and is cleared only by glomerular filtration, i.e. no non-renal elimination of the substance. Accurate measurement of GFR is methodologically difficult in vivo so surrogate estimates such as creatinine clearance rate and prediction formulae are more commonly used in routine clinical practice. Various equations have been derived to estimate GFR in non-obese populations but there are discrepancies between different methods. The Cockcroft—Gault (CCG) formula adjusted for lean body mass (CCGLBM) is believed superior to these other equations for accurately estimating GFR in obese patients when compared to the gold standard GFR estimation method of radioisotope measurements to determine creatinine clearance [4—10]. However measuring lean body mass (LBM) can be problematic in the obese and requires other equipment such as bioelectrical impedance analysis, a technique not likely available in an Emergency Department or general hospital ward. The question arises — what other estimate of GFR is easily generated at the bedside and also approximates the CCGLBM formula for estimating GFR in the obese over a wide range of renal function? This study aimed to determine an estimate that is suitable for the obese which can be generated more easily than the CCGLBM.
M.T. Nguyen et al. Comprehensive Metabolic Care Clinic at the Royal Adelaide Hospital. Only those with a pacemaker and those weighing over 200 kg were excluded from this study. There were 29% with diabetes mellitus and 50% with hypertension, and 28% were on angiotensin converting enzyme inhibitors or angiotensin 2 receptor blockers. Subjects were unlikely to yet have started a significant dietary treatment such as high protein meal or weight loss because all measurements were taken at patients’ first visit to the clinic. No patient was studied after gastric surgery. Anthropometric, clinical and biological characteristics were recorded for each patient. Weight measurements including LBM were obtained using an electronic scale (Tanita InnerScan, Tanita corp., Tokyo, Japan). The Tanita InnerScan is a single frequency bioelectrical impedance analysis device that uses a tetrapolar footpad-style electrode arrangement and has a capacity of 200 kg. In accordance with the manufacturer’s instructions, the subjects stood on the metal footpads in bare feet, and measurements were determined using predication equations supplied by the manufacturer. All methods of assessing body composition in this patient group are difficult. This method was chosen for feasibility and patient acceptability without significant compromise in accuracy [11,12]. These data were used to estimate each patient’s GFR according to a series of formulae described in Table 1. The value for GFR derived from each formula was plotted against the same patient’s GFR estimated by the CCGLBM equation using a Bland—Altman (BA) analysis. The means of the GFR estimates by the two different equations were compared as was the difference between the two estimates over the observed range of renal function. Fixed and proportional biases were assessed by t-test and regressions analysis. Data are presented as means ± standard deviation unless otherwise stated. Statistical comparisons were made using correlation analysis and independent sample t-tests. A p value less than 0.05 was used to define the level of statistical significance. Approval for this study was obtained from the Royal Adelaide Hospital Research Ethics Committee.
Results Methods Eighty-two obese Caucasian patients were prospectively recruited sequentially from the
Anthropometric, clinical and biological characteristics of the population are shown in Table 2. The BA analysis results are shown in Fig. 1. All equations except for the CCGIBW showed a significant
Please cite this article in press as: Nguyen MT, et al. Estimating glomerular filtration rate in obese subjects. Obes Res Clin Pract (2014), http://dx.doi.org/10.1016/j.orcp.2014.04.001
GFR estimation equations. Numeric Expression
Cockcroft—Gault formula adjusted for lean body mass (CCGLBM) [13] Cockcroft—Gault formula (CCG) [14]
(140−Age (year))×LBM (kg)×Gender Value Gender 72 Serum creatinine(umol/L)
Cockcroft—Gault formula adjusted for ideal body weight (CCGIBW) Cockcroft—Gault formula adjusted for body surface area (CCGBSA) [8]
(140−Age(years))×IBW (kg)×Gender Value Gender Serum Creatinine (umol/L)
Modified Diet in Renal Disease formula (MDRD) [15]
value is 0.85 if female and 1 if male.
(140−Age(years))×Actual Weight(kg)×Gender Value Gender Serum Creatinine(umol/L)
value is 0.85 if female and 1 if male.
value is 0.85 if female and 1 if male.
× measured using the Du Bois formula (140−Age(years))×Actual Weight(kg)×Gender Value Serum Creatinine(umol/L)
ARTICLE IN PRESS
Name of equation
1.73 Gender BSA
value is 0.85 if female and 1 if male. BSA in m2
32, 788 × Serum Creatinine (umol/L)−1.154 × Age(years)−0.203 × Constant1 × Constant2Constant1 is 0.742 if female and 1 if male. Constant2 is 1.212 if black. (146−Age)×[(0.287×Weight)+(9.74×Height2 )] 60×Serum creatinine (mg/dL)
Salazar and Corcoran formulas (SaC) [16]
(137−Age(years))×[(0.285×Weight (kg))+(12.1×Height(m)2 )] 51×Serum Creatinine (mg/dL)
Chronic Kidney Disease Epidemiology Collaboration formula (CKD-EPI) [17]
(mg/dL)) (mg/dL)) 141 × min (Serum creatinine , 1 × max (Serum Creatinine ,1 × 0.993Age(years) ‘‘k’’ is 0.7 for k k females and 0.9 for males. ‘‘a’’ is −0.329 for males and −0.411 for males.
Mayo Quadratic [18]
exp 1.911 +
a
5.249 Serum creatinine(mg/dL)
−
×
2.114 (Serum creatinine (mg/dL))2
ORCP-375; No. of Pages 6
Estimating GFR in obese subjects
−1.209
− 0.00686 × Age(years) − Constant Constant is
0.205 if female and 0 if male.
xxx.e3
Please cite this article in press as: Nguyen MT, et al. Estimating glomerular filtration rate in obese subjects. Obes Res Clin Pract (2014), http://dx.doi.org/10.1016/j.orcp.2014.04.001
Table 1
ORCP-375; No. of Pages 6
ARTICLE IN PRESS
xxx.e4 Table 2
M.T. Nguyen et al. Anthropometrical and biological characteristics of the obese population (N = 82).
Characteristics
Mean
SD
Range
Fixed p value
Proportional p value
Age (years) Weight (kg) Height (cm) Gender (Female %) BMI (kg/m2 ) LBM (kg) BSA (m2 ) Serum creatinine (mol) CCGLBM (ml/min) CCG (ml/min) CCGIBW* (ml/min) CCGBSA (ml/min/1.73 m2 ) MDRD (ml/min/1.73 m2 ) SaC (ml/min) CKDEPI (ml/min/1.73 m2 ) Mayo Quadratic (ml/min)
43.1 132.1 168.4 72.0 47.0 60.0 2.3 70.3 98.2 218.4 100.5 159.0 101.9 162.1 100.0 113.5
12.7 26.9 9.4 — 8.0 11.5 0.3 25.7 33.6 85.5 32.8 52.1 29.6 55.7 22.8 13.2
20.0—76.0 80.3—197.8 147.0—192.0 — 30.4—39.8 40.3—94.6 1.7—3.0 41.0—226.0 20.9—214.8 44.2—461.3 24.2—186.2 33.3—317.5 20.4—178.8 35.9—311.1 19.8—140.8 87.4—152.2
— — — — — — — — —
