

Year : 2014  Volume
: 25
 Issue : 5  Page : 10041010 

Comparison of the performance of the updated Schwartz, combined Schwartz and the Grubb glomerular filtration rate equations in a general pediatric population 

Alaleh Gheissari^{1}, Peyman Roomizadeh^{2}, Roya Kelishadi^{3}, Amin Abedini^{4}, Shaghayegh HaghjooyJavanmard^{5}, SeyedHossein Abtahi^{4}, Bahareh Mehdikhani^{6}
^{1} Department of Pediatric Nephrology; Isfahan Kidney Diseases Research Center, Isfahan University of Medical Sciences, Isfahan, Iran ^{2} Isfahan Kidney Diseases Research Center; Medical Students Research Center, Isfahan University of Medical Sciences, Isfahan, Iran ^{3} Pediatrics Department, Faculty of Medicine and Child Growth and Development Research Center, Isfahan University of Medical Sciences, Isfahan, Iran ^{4} Medical Students Research Center, Isfahan University of Medical Sciences, Isfahan, Iran ^{5} Applied Physiology Research Center, Department of Physiology, Isfahan University of Medical Sciences, Isfahan, Iran ^{6} Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran
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Date of Web Publication  2Sep2014 




Abstract   
To determine the performance of the updated Schwartz, combined Schwartz and Grubb glomerular filtration rate (GFR) equations in a relatively large number of healthy children with no known renal disease, we studied 712 students aged between seven and 18 years from the Isfahan province of Iran by random cluster sampling between 2009 and 2010. Blood investigations included blood urea nitrogen, creatinine and cystatin C. For each participant, GFR was calculated based on the three equations. We used BlandAltman plots and weighted kappa statistics to compare the performance of the study equations. The mean age of the children was 12.2 ± 2.4 years. A high concordance in estimating GFR (mean difference: 0 ± 12.7 mL/min/1.73 m ^{2} ) and a very good agreement in defining chronic kidney disease (CKD) and nonCKD individuals (weighted kappa: 0.85; 95% confidence intervals: 0.691) were observed between the updated Schwartz and the combined Schwartz equations. Poor agreement was observed between the Grubb equation and two Schwartz equations in estimating GFR and defining CKD. There was no systematic deviation between the updated Schwartz and the combined Schwartz equations in children with normal renal function. The Grubb equation was highly inconsistent with both Schwartz equations in this population. We conclude that the updated Schwartz equation is simpler and more accessible than the combined Schwartz equation in daily clinical practice and CKD screening programs.
How to cite this article: Gheissari A, Roomizadeh P, Kelishadi R, Abedini A, HaghjooyJavanmard S, Abtahi SH, Mehdikhani B. Comparison of the performance of the updated Schwartz, combined Schwartz and the Grubb glomerular filtration rate equations in a general pediatric population. Saudi J Kidney Dis Transpl 2014;25:100410 
How to cite this URL: Gheissari A, Roomizadeh P, Kelishadi R, Abedini A, HaghjooyJavanmard S, Abtahi SH, Mehdikhani B. Comparison of the performance of the updated Schwartz, combined Schwartz and the Grubb glomerular filtration rate equations in a general pediatric population. Saudi J Kidney Dis Transpl [serial online] 2014 [cited 2021 Dec 3];25:100410. Available from: https://www.sjkdt.org/text.asp?2014/25/5/1004/139890 
Introduction   
Glomerular filtration rate (GFR) is widely accepted as the best overall indicator of renal function. ^{[1]} The reference methods for the measurement of the GFR require determination of renal clearance of exogenous substances such as inulin, Cr51EDTA, iohexol and iothalamate. These methods are invasive, expensive and hard to employ in daily clinical practice; therefore, the GFR is routinely estimated by measuring serum concentration of endogenous markers of renal function. ^{[2]} Serum creatinine is the most commonly used endogenous marker for assessment of the GFR worldwide. However, in recent years, a novel marker of renal function, cystatin C, is suggested as a more sensitive marker than serum creatinine in the assessment of GFR. ^{[3],[4]}
The original Schwartz equation (developed in 1976) was the most popular GFR equation for children below 18 years of age for the past three decades. ^{[5]} This equation was developed with creatinine measured by the Jaffé reaction. ^{[5]} However, during these years, the laboratory methods for the measurement of serum creatinine have been widely replaced with new enzymatic methods (isotope dilution mass spetrometry). The original Schwartz equation is believed to overestimate GFR when creatinine is measured by the enzymatic methods. ^{[2]} Accordingly, in 2009, Schwartz et al ^{[6]} proposed an updated version of their original equation that was developed based on the enzymatic method of creatinine measurement. In addition to their "updated" equation, they also developed a new GFR equation that is based on serum levels of creatinine, blood urea nitrogen (BUN) and cystatin C (named as the "combined" Schwartz equation). ^{[6]}
Beside the equations proposed by Schwartz et al, there are several other cystatin Cbased GFR equations used in the pediatric population. Among the existing equations, only the equation proposed by Grubb et al ^{[7]} is developed with a cystatin C measurement method similar to the method used in the 2009 Schwartz et al study. ^{[6]} This methodological similarity has made the comparison between these equations possible.
We aimed in this study to compare the updated Schwartz, the combined Schwartz and the Grubb equations in a relatively large number of healthy children with no known renal disease in estimating the GFR and categorizing individuals into chronic kidney disease (CKD) and nonCKD groups in this population.
Patients and Methods   
The data used in this study were obtained from a baseline survey of the "Childhood and Adolescence Surveillance and Prevention of Adult Noncommunicable Disease" (CASPIAN Study). The third phase of this nationwide schoolbased health survey was conducted in 5028 Iranian students aged seven to 18 years who were selected by multistage random cluster sampling from urban and rural areas of 27 provinces of Iran between 2009 and 2010. The present paper describes the findings of 712 school students from Isfahan, a large province located in the central part of the country. A detailed description about the procedure of data gathering and sample collection of the Caspian studies has been characterized elsewhere. ^{[8]} In brief, after complete explanation of the study objectives and protocol to the students and their parents, a team of trained nurses collected the demographic and the clinical data of the eligible subjects including age, sex, height, weight and blood pressure. Fasting blood samples were drawn from the participants and centrifuged for 10 min at 3000 rpm within 30 min of venipuncture in the Isfahan central provincial laboratory, where biochemical measurements were carried out.
Written informed consents were obtained from the parents/caregivers besides oral assent from the students before enrollment in the study. The study was approved by the institutional review boards, and adhered to the tenets of Helsinki declaration.
Serum creatinine and BUN levels were measured by the enzymatic methods on a Hitachi 917 autoanalyzer. Serum cystatin C levels were measured by the particleenhanced immunoturbidimetric method (Dako, Glostrup, Denmark). ^{[9]} Cystatin C levels lower than 1.38 mg/L were considered normal in the general population. ^{[10]}
To calculate the GFR for each subject, we applied the following equations:
The "updated" Schwartz equation: ^{[6]}
GFR (mL/min/1.73 m ^{2} ) = 0.413 × height (cm)/ serum creatinine (mg/dL)
The "combined" Schwartz equation: ^{[6]}
GFR (mL/min/1.73 m ^{2} ) = 39.1 × [height (m)/creatinine (mg/dL)] ^{0.516} × [1.8/cystatin C (mg/L] ^{0.294} × [30/BUN (mg/dL)] ^{0.169} × (1.099) ^{if} ^{male} × [height (m)/1.4] ^{0.188}
The Grubb equation: ^{[7]}
GFR (mL/min/1.73 m ^{2} ) = 84.69 [cystatin C(mg/L)] ^{1.680} × 1.384 ^{if <14 years}
According to the estimated GFR by each equation, the participants were categorized as CKD group (defined as GFR <60 mL/min/1.73 m ^{2} ) or nonCKD group (defined as GFR >60 mL/min/1.73 m ^{2} ).
Statistical Analysis   
Continuous values are expressed as mean ± SD and categorical variables are presented as numbers (percentage). The level of agreement in estimating GFR between equations was examined using the BlandAltman analysis. ^{[11]} Based on this statistical method, the limits of agreement were determined by the mean difference ± 1.96 × SD of the percentage of changes. Weighted kappa statistics were used to assess the agreement between the equations in categorizing individuals as CKD or nonCKD. Statistical analyses were carried out using the SPSS software version 19.0 (SPSS, Chicago, IL, USA) and MedCalc version 12.1.4.0 (MedCalc Software, Mariakerke, Belgium). Pvalue <0.05 was considered to be statistically significant.
Results   
Of the 712 included children, 377 (52.9%) were male. The mean age was 12.2 ± 2.4 years (range: 718) and the mean body mass index was 18.2 ± 3.8 kg/m ^{2} . Detailed demographic and clinical characteristics of the participants are presented in [Table 1]. The mean GFR was 99.7 ± 19.7 mL/min/1.73 m ^{2} by the combined Schwartz equation, 99.7 ± 19.7 mL/min/1.73 m ^{2} by the updated Schwartz equation and 168 ± 81.6 mL/min/1.73 m ^{2} by the Grubb equation. [Figure 1] shows the distribution of the estimated GFRs by each equation. The Grubb equation resulted in a considerably wider distribution of values at both the upper and the lower levels of GFR values in comparison with the Schwartz equations. Such a difference in the GFR distribution was due to the larger standard deviation of the GFR values estimated by the Grubb equation. [Figure 2] shows the BlandAltman plots for the agreement between the GFR values by each equation. We found a high level of agreement between the combined Schwartz and the updated Schwartz equations (mean difference: 0 ± 12.7 mL/min/ 1.73 m ^{2} ). Agreements between the combined Schwartz and Grubb equations (mean difference: 68.4 ± 68.3 mL/min/1.73 m ^{2} ) and between the updated Schwartz and the Grubb equations (mean difference: 68.4 ± 76.0 mL/min/1.73 m ^{2} ) were poor. The frequency of CKD was 7%, 1.7% and 1.3%, based on the Grubb, the combined Schwartz and the updated Schwartz equations, respectively. [Table 2] shows the overlaps of individuals categorized as CKD and nonCKD based on each equation and also the corresponding weighted kappa coefficients quantifying the inter and intrarater reliability assessments. The weighted kappa statistics revealed a very good agreement between both Schwartz equations in categorizing individuals in the CKD and nonCKD groups ( = 0.85; 95% CI: 0.691). On the other hand, the Grubb equation showed a fair agreement with both Schwartz equations in categorizing individuals as CKD and nonCKD [Table 2].  Figure 1: The BoxandWhisker plots of the distribution of the estimated GFR with the use of different equations. The BoxandWhisker plots display the 25^{th}, 50^{th} and 75^{th} percentile by the lines at the bottom, middle and top of the box. The brackets show the 95% range.
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 Figure 2. Bland–Altman plots of comparison between equations in estimating GFR. (A) Comparison between combined Schwartz and updated Schwartz equations. (B) Comparison between combined Schwartz and Grubb equations. (C) Comparison between updated Schwartz and Grubb equations. The continuous line shows the mean difference between the two equations and the dashed lines show the limits of agreement, defined as mean ± 1.96 SD.
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 Table 1: Demographic, biochemical and renal characteristics of the study participants.
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 Table 2: Overlaps of CKD or nonCKD individuals based on the study equations and weighted kappa coefficients quantifying inter and intrarater reliability assessment (n = 712).
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Discussion   
In this study, we found that both 2009 Schwartz equations were in high concordance in estimating GFR and defining individuals as CKD or nonCKD, while there was a limited agreement between the Schwartz equations and the Grubb formula. These findings suggest that there is no systematic deviation between the Schwartz equations and that they can be used interchangeably in daily clinical practice. The updated equation only requires the values of serum creatinine and height and, therefore, is simpler than the combined equation. The updated equation can be considered more accessible and costbeneficial in daily pediatric practice and also in large CKD screening programs.
In our study, the Grubb equation appeared to be highly inconsistent with the two Schwartz equations. A similar observation was found by Fadrowski et al, ^{[12]} who compared the performance of a number of GFR equations in a large sample of American adolescents aged 1217 years. In their study, the median GFR estimated by the updated Schwartz, combined Schwartz and Grubb equations were 96.6, 96.6 and 130.1 mL/min/1.73 m ^{2} , respectively.
In our study, the Grubb equation yielded a higher prevalence of CKD in comparison with the Schwartz equations. Such apparent discrepancies between the Schwartz and the Grubb equations are probably due to the differences in the characteristics of the sampled populations of the Schwartz et al ^{[6]} and the Grubb et al ^{[7]} studies. It is well established that the demographic and the clinical status of the population significantly affect the accuracy of the obtained equation for estimation of the GFR. ^{[13],[14]}
During the past decade, several other creatinine and/or cystatin Cbased GFR equations have been proposed for children (e.g., Zappitelli et al, ^{[15]} Bouvet et al, ^{[16]} Filler et al ^{[17]} and Leger et al ^{[18]} ). However, all such equations originated from specific patients with various types of kidney diseases and, therefore, their extrapolation to the general pediatric population is a matter of debate. ^{[2],[19]} Furthermore, the differences in the cystatin C assay methods used in these studies rendered the comparison between the existing equations difficult. It is important to note that the equations by Schwartz et al ^{[6]} and Grubb et al ^{[7]} are developed using particleenhanced turbidimetric immunoassay (PETIA) for cystatin C measurement. On the other hand, the majority of the other exiting cystatin Cbased equations used the particleenhanced nephelometric immunoassay (PENIA) method. ^{[15],[16],[17],[18]} Because we aimed to investigate the performance of the combined Schwartz equation, we used PETIA for cystatin C measurement in our study. With respect to the lack of a uniform reference standard for the calibration of PETIA and PENIA at the present time, ^{[12]} we were able to include only the Grubb equation from several existing equations for comparison in this study.
The updated Schwartz equation is validated in children with normal renal function. ^{[20]} The United States National Kidney Disease Education Program (NKDEP) has suggested this equation as the "best creatinine basedGFR equation for all children." ^{[21]} Nevertheless, at the present time, a global consensus on an ideal GFR equation in children does not exist. In 2002, the National Kidney Foundation (KDOQI) recommended the use of the original Schwartz equation in all children. ^{[22]} However, due to dramatic changes in the laboratory assay methods and considering several new GFR equations introduced during the past decade, there is an essential need to update the KDOQI guidelines for an allpurpose GFR equation for children. Further studies with a reference GFR are warranted to investigate the accuracy of the existing equations in healthy children with normal renal function.
The main limitation of our study was the lack of a gold standard measurement of GFR for the study subjects. Given this, we were not able to determine the most accurate equation in our population. It should be considered that it was difficult to obtain reference GFR in our study as the ethical considerations may preclude the exposure of healthy children with no known renal disease to radioactive radiations that are required for determination of reference GFR.
In conclusion, in this study, we demonstrated a high concordance and agreement between the two 2009 Schwartz equations in estimating GFR and defining CKD individuals in the general pediatric population. The updated equation is more easily implemented in daily clinical practice. More studies with reference GFR are needed to evaluate the accuracy of the existing GFR equations in children with normal renal function.
Conflict of Interest
The authors declare that they have no conflict of interest.
References   
1.  Stevens LA, Coresh J, Greene T, Levey AS. Assessing kidney functionmeasured and estimated glomerular filtration rate. N Engl J Med 2006;354: 247383. 
2.  Schwartz GJ, Work DF. Measurement and estimation of GFR in children and adolescents. Clin J Am Soc Nephrol 2009;4:183243. 
3.  Dharnidharka VR, Kwon C, Stevens G. Serum cystatin C is superior to serum creatinine as a marker of kidney function: A metaanalysis. Am J Kidney Dis 2002;40:2216. 
4.  Roos JF, Doust J, Tett SE, Kirkpatrick CM. Diagnostic accuracy of cystatin C compared to serum creatinine for the estimation of renal dysfunction in adults and childrena metaanalysis. Clin Biochem 2007;40:38391. 
5.  Schwartz GJ, Haycock GB, Edelmann CM Jr, Spitzer A. A simple estimate of glomerular filtration rate in children derived from body length and plasma creatinine. Pediatrics 1976; 58:25963. [PUBMED] 
6.  Schwartz GJ, Muñoz A, Schneider MF, et al. New equations to estimate GFR in children with CKD. J Am Soc Nephrol 2009;20:62937. 
7.  Grubb A, Nyman U, Björk J, et al. Simple cystatin Cbased prediction equations for glomerular filtration rate compared with the modification of diet in renal disease prediction equation for adults and the Schwartz and the CounahanBarratt prediction equations for children. Clin Chem 2005;51:142031. 
8.  Kelishadi R, Motlagh ME, Roomizadeh P, et al. First report on path analysis for cardiometabolic components in a nationally representative sample of pediatric population in the Middle East and North Africa (MENA): the CASPIANIII Study. Ann Nutr Metab 2013;62 (3):25765. 
9.  KyhseAndersen J, Schmidt C, Nordin G, et al. Serum cystatin C, determined by a rapid, automated particleenhanced turbidimetric method, is a better marker than serum creatinine for glomerular filtration rate. Clin Chem 1994;40:19216. 
10.  Bökenkamp A, Domanetzki M, Zinck R, Schumann G, Brodehl J. Reference values for cystatin C serum concentrations in children. Pediatr Nephrol 1998;12: 1259. 
11.  Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986;1:30710. [PUBMED] 
12.  Fadrowski JJ, Neu AM, Schwartz GJ, Furth SL. Pediatric GFR estimating equations applied to adolescents in the general population. Clin J Am Soc Nephrol 2011;6:142735. 
13.  Sharma AP, Yasin A, Garg AX, Filler G. Diagnostic accuracy of cystatin Cbased eGFR equations at different GFR levels in children. Clin J Am Soc Nephrol 2011;6:1599608. 
14.  Filler G, Foster J, Acker A, Lepage N, Akbari A, Ehrich JH. The CockcroftGault formula should not be used in children. Kidney Int 2005;67: 23214. 
15.  Zappitelli M, Parvex P, Joseph L, et al. Derivation and validation of cystatin Cbased prediction equations for GFR in children. Am J Kidney Dis 2006; 48:22130. 
16.  Bouvet Y, Bouissou F, Coulais Y, et al. GFR is better estimated by considering both serum cystatin C and creatinine levels. Pediatr Nephrol 2006;21: 1299306. 
17.  Filler G, Lepage N. Should the Schwartz formula for estimation of GFR be replaced by cystatin C formula? Pediatr Nephrol 2003;18:9815. 
18.  Léger F, Bouissou F, Coulais Y, Tafani M, Chatelut E. Estimation of glomerular filtration rate in children. Pediatr Nephrol 2002;17:9037. 
19.  Bacchetta J, Cochat P, Rognant N, Ranchin B, HadjAissa A, Dubourg L. Which creatinine and cystatin C equations can be reliably used in children? Clin J Am Soc Nephrol 2011;6:55260. 
20.  Staples A, LeBlond R, Watkins S, Wong C, Brandt J. Validation of the revised Schwartz estimating equation in a predominantly nonCKD population. Pediatr Nephrol 2010;25: 23216. 
21.  National Kidney Disease Education Program (NKDEP); GFR Calculator for Children: Bedside IDMStraceable Schwartz GFR Calculator for Children. April 25, 2012. Available from: http://nkdep.nih.gov/labevaluation/gfrcalculators/childrenconventionalunit.asp [Last accessed on 2012 May 19]. 
22.  K/DOQI clinical practice guidelines for chronic kidney disease: Evaluation, classification, and stratification. Am J Kidney Dis 2002;39(2 Suppl 1): S1266. 
Correspondence Address: Dr. Peyman Roomizadeh Isfahan Kidney Diseases Research Center, Isfahan University of Medical Sciences and Health Services, Isfahan Iran
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DOI: 10.4103/13192442.139890 PMID: 25193898
[Figure 1], [Figure 2]
[Table 1], [Table 2] 











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