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Table of Contents
Year : 2021  |  Volume : 10  |  Issue : 1  |  Page : 9-14

Comparison of estimated glomerular filtration rate equations in elderly with chronic kidney disease

1 Department of General Medicine, Nizam's Institute of Medical Sciences, Hyderabad, Telangana, India
2 Department of Nephrology, Nizam's Institute of Medical Sciences, Hyderabad, Telangana, India

Date of Submission01-Feb-2020
Date of Decision23-Apr-2020
Date of Acceptance11-Aug-2020
Date of Web Publication4-Mar-2021

Correspondence Address:
Swaroopa Deme
Department of General Medicine, Nizam's Institute of Medical Sciences, Punjagutta, Hyderabad 500 082, Telangana
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/JCSR.JCSR_8_20

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Background: Chronic kidney disease (CKD) a growing epidemic in India with limited studies addressing the problem of ideal equation for estimated glomerular filtration rate (eGFR) among elderly Indian patients. Currently, eGFR is calculated employing the CKD Epidemiology Collaboration (CKD-EPI) equations of which the combination of creatinine and cystatin-c (eGFR cr-cys) is recommended as more accurate. However, preferred equations and filtration markers in elderly individuals are debated.
Methods: The present prospective observational study conducted from 2012 to 2014 at our tertiary care centre, aimed at identifying the best filtration marker and eGFR equation for elderly CKD patients. One hundred and seven elderly CKD patients were studied. Comparison of eGFR equations derived from modification of diet in renal disease (MDRD) and CKD-EPI, based on creatinine and cystatin-c was done.
Results: Median creatinine was 2.4, and median cystatin-c was 1.9. On comparing the correlation between all four equations by spearman correlation coefficient, difference was noted. eGFR by EPI-creatinine and cystatin-c correlated with all other three equations with correlation coefficient of 0.84 for both MDRD, EPI-creatinine and 0.82 for EPI-cystatin-c equations, respectively.
Conclusions: Of the four equations for eGFR, EPI-cystatin-c and creatinine equation showed better correlation with all other equations, hence might be the better equation for confirmation and classification of the elderly CKD patients.

Keywords: Chronic kidney disease, creatinine, cystatin-c, estimated glomerular filtration rate, elderly

How to cite this article:
Deme S, Neelam PB, Killi S, Raju SB, Raju Y S. Comparison of estimated glomerular filtration rate equations in elderly with chronic kidney disease. J Clin Sci Res 2021;10:9-14

How to cite this URL:
Deme S, Neelam PB, Killi S, Raju SB, Raju Y S. Comparison of estimated glomerular filtration rate equations in elderly with chronic kidney disease. J Clin Sci Res [serial online] 2021 [cited 2021 Jun 25];10:9-14. Available from: https://www.jcsr.co.in/text.asp?2021/10/1/9/310770

  Introduction Top

Due to the increasing prevalence of diabetes, hypertension and obesity, there will be a higher burden of chronic kidney disease (CKD) in developing countries,[1] and the prevalence of CKD is rising in India and the predominant etiologies include diabetic nephropathy, glomerulonephritis, hypertension-associated CKD (includes vascular and ischaemic), autosomal dominant polycystic kidney disease and tubulointerstitial nephropathy.[2] Measuring glomerular filtration rate (GFR) by the clearance of some exogenous markers is not suitable in routine clinical practice, though they are the gold standard methods.[3] Despite all known disadvantages, predictive equations based on creatinine, such as the Cockcroft-Gault (C and G) formula and abbreviated modification of diet in renal disease (MDRD) formula, have become the most commonly used marker to estimate GFR in clinical practice and most studies.[4],[5] CKD is common in elderly individuals who are known to have lower muscle mass and protein intake. This may lead to more significant bias in calculating GFR based on serum creatinine;[6] hence, there is debate about the accuracy of GFR estimates in this important subgroup of the population.

Cystatin-c is a potential alternative to serum creatinine for estimating GFR with the advantage of accuracy and not being affected by muscle mass and age of individuals.[7] Cystatin C has its limitations being a costly investigation compared to creatinine and is influenced by C-reactive protein level, thyroid function, concomitant corticosteroid treatment, pregnancy and underlying malignancy[8] and were included in the exclusion criteria. Several serum cystatin-c-based equations have been developed and proposed to estimate the GFR. CKD Epidemiology Collaboration (CKD-EPI) formula is one of the proposed new equations that use both serum creatinine and serum cystatin-c (CKD-EPI creatinine and cystatin formula) for estimation of kidney function.[9],[10] Several reports have demonstrated that the estimated glomerular filtration rate (eGFR) based on the combination of both standardised serum creatinine and cystatin-c is more accurate than eGFR based on either marker alone.[11] Still, there are few studies using standardised serum creatinine and cystatin-c to evaluate these equations in elderly individuals[12] and no studies among the Indian elderly CKD patients. This study aims to compare two serum creatinine-based equations (MDRD formula and CKD-EPI formula), CKD-EPI creatinine and cystatin formula and the simple cystatin-c formula among elderly CKD patients.

  Material and Methods Top

This was a prospective observational study carried out between 2012 and 2014. We enrolled elderly patients with CKD attending either to outpatient or admitted in the departments of Nephrology and General Medicine. Institutional Review Board approval was obtained. Written informed consent was obtained from all the study participants.

People aged ≥60 year, with CKD, attending to Nizam's Institute of Medical Sciences (NIMS), Hyderabad during the study period who were willing to participate in the study were included in the study after obtaining written informed consent.

End-stage renal disease patients on maintenance haemodialysis or continuous ambulatory peritoneal dialysis, moribund patients, patients on steroids, pregnant women, patients with abnormal thyroid function tests and with underlying malignancies were excluded.

The equations employed for calculating eGFR values in the study are mentioned in [Table 1].
Table 1: Equations employed for the estimation of GFR and their formulae

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All patients were subjected to comprehensive geriatric assessment including a full medical history and examination, and laboratory investigations included a complete blood picture, total serum proteins, serum albumin, complete urine examination, serum calcium, phosphorus, uric acid, thyroid profile, iron studies, vitamin D, serum creatinine and cystatin c and ultrasonography of the abdomen. Age was recorded from the birth records; weight was measured by a digital weighing scale.

Serum creatinine levels of the study participants were measured by kinetic modification of the Jaffe procedure on AU 680 autoanalyzer (Beckman Coulter CHASKA, USA). Serum Cystatin-c levels were measured by immunoassay on the COBAS INTEGRA systems (Roche diagnostics, Switzerland) with the normal measuring range determined as 0.4–8.0 mg/L.

Statistical analysis

Descriptive statistical analysis has been carried out on the continuous variables, and frequency analysis carried out on categorical variables. Data normality was tested and the continuous variables are expressed as median with interquartile range (IQR) for the non-normally distributed variables. Spearman's correlation, a nonparametric test was used to measure the degree of association between various equations employed in calculating eGFR. Statistical analysis was carried out using SPSS version 20 statistical software (IBM Corp, New York, USA).

  Results Top

As shown in [Table 2], a total of 107 patients were included in our study, of them, 72% were between 60 and 69 years, which was the majority age group, 70–79 years and >80 years age group contributed to 18.7% and 9.4%, respectively. Male-to-female ratio was 3.1:1. Between 60 and 69 years and 80 years and above, males predominated with 55.1% and 7.5%, respectively, and among the age group of 70–79 years, females predominated with 61%. Out of 107 patients, 2 (1.9%) were in Stage I CKD, 7 (6.5%) were in Stage II, 41 (38.3%) were in Stage III, 40 (37.4%) were in Stage IV and 17 (15.9%) were in Stage V CKD estimated as per EPI-creatinine and cystatin-c equation.
Table 2: Age group and gender distribution of the chronic kidney disease subjects

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[Figure 1] is the box and whisker plot showing the median eGFR values along with the IQRs. [Table 3] shows the mean, median values of creatinine and cystatin-c along with the mean, median values of the eGFR calculated based on the respective MDRD, EPI creatinine, EPI cystatin-c, EPI creatinine and cystatin-c equations.
Figure 1: eGFR by different equations. Box and whisker plot representing the median values of the estimated glomerular filtration rate along with the interquartile ranges derived by different equations. Min = Minimum; Q1 = Quartile 1; Med = Median; Q3 = Quartile 3; Max = Maximum; Std = Standard deviation; Avg = Average (mean); eGFR = Estimated glomerular filtration rate; CKD EPI = Chronic kidney disease epidemiology collaboration; MDRD = Modification of diet in renal disease study

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Table 3: Complete demographic and descriptive data of the variables in the study group

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On comparing all four equations with each other by spearman correlation coefficients [Table 4], there was no statistically significant difference in correlation, but they differed in their strength of the correlation [Figure 2].
Table 4: Comparing the correlation between 4 different equations of estimated glomerular filtration rate with each other

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Figure 2: Correlation between different equations of eGFR with each other. Scatter plot showing that there is a linear correlation between the MDRD equation and EPI-creatinine equations. There is minimal scatter between EPI creatinine and cystatin-c equation and the other three equations. There is significant scatter between EPI-cystatin-c equation and MDRD, EPI-creatinine equations. eGFR = Estimated glomerular filtration rate; EPI = Epidemiology; MDRD = Modification of diet in renal disease

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The eGFR by MDRD equation better correlated with eGFR by EPI-creatinine equation with 0.99 being the strength of correlation and with a linear correlation between the two equations. eGFR by EPI-creatinine correlated with EPI-creatinine and cystatin-c with a coefficient of 0.84. eGFR by EPI-cystatin-c better correlated with eGFR by EPI-Creatinine and cystatin-c with 0.82 being the correlation coefficient. It weakly correlated with EPI-Creatinine, MDRD equations with correlation coefficients being 0.44 and 0.45, respectively, suggesting that there was a significant difference in the strength of correlation between eGFR estimated using creatinine and cystatin-c. eGFR by EPI-creatinine and cystatin-c correlated with all other three equations with a correlation coefficient of 0.84 for MDRD and EPI-creatinine and 0.82 for EPI-cystatin-c equations, respectively.

  Discussion Top

Early impaired kidney function often has no apparent symptoms, which leads to delayed diagnosis, particularly in the elderly.[13] Therefore, accurate assessment of kidney function is essential. A reduction in GFR to <60 ml/min/1.73 m2 for 3 months or longer is diagnostic for CKD[14] and is associated with an increased risk of adverse outcomes, including death.[14],[15]

The primary limitation of creatinine is that levels are determined not only by GFR but also by muscle mass and dietary intake.[16] When obesity is present, there was no reliable estimation of eGFR by using either the CG or MDRD formula, suggesting that high body mass index (BMI) limits eGFR measurement.[17] Furthermore, sarcopenia, a common condition in the elderly, and low BMI contributes to abnormally low creatinine levels, resulting in falsely high values of eGFR for equations based on creatinine, and among patients with CKD, loss of lean body mass, especially appendicular skeletal mass, was significantly related to GFR decline.[18] Creatinine excretion is not only due to filtration (90%–95%) by the kidney but also to secretion (5%–10%) by the distal tubule. Furthermore, there is extrarenal elimination for creatinine. Cystatin-c has desirable traits as a marker of GFR.[19],[20] It is thought to be filtered solely by the glomerulus, entirely reabsorbed by the tubules and then catabolized, not secreted by the renal tubules[20] and generated at a constant rate by all cells in the body, although it has few limitations.[8]

Among 107 enrolled patients, 81 were male with most of the patients in the age group of 60–69 years and mean age of 67.3 years. The male-to-female ratio is 3.1:1. which was comparable to the results of another study[21] from Tiruchirappalli, South India (n = 106 CKD patients) where the male-to-female ratio 3.1:1 was same as that observed in our study.

Out of 107, 74 (69.2%) patients had hypertension, and 65 (60.7%) patients had diabetes mellitus, which are the most common causes of CKD, and the findings were comparable to findings of another study.[22]

In the present study, minimum serum creatinine (mg/dL) was 0.7, the maximum was 9.7 with median creatinine of 2.4. Minimum and maximum cystatin-c levels (mg/L) were 0.4 and 4.5, respectively, with a median cystatin-c (mg/L) of 1.9; these values were comparable to that reported in another study[10] where median serum creatinine and serum cystatin-c values were 2.1 mg/dL and 1.8 mg/L, respectively.

In a study[23] comparing the eGFR from creatinine and cystatin-c by different equations using creatinine alone, cystatin-c alone and a combination of creatinine and cystatin-c. The authors[23] concluded that the combination of serum creatinine and serum cystatin-c is more accurate than either marker alone for estimating GFR; a similar outcome is observed in our study.

A study[24] compared CKD-EPI cystatin-c and creatinine glomerular filtration rate estimation equations in Asian Indians. The authors[24] concluded that using serum cystatin-c resulted in widely varying eGFR, which significantly affected the classification of CKD. Another study[25] comparison of cystatin C and creatinine-based eGFR equations among elderly CKD; they concluded that decreased renal function among the elderly varies considerably depending on the prediction formula used. Variation in creatinine metabolism among elderly co-morbid patients and the critical dependence on the serum creatinine assay and exact calibration make the use of creatinine-based formulae to predict GFR questionable in geriatric clinical practice. In this setting, Cys C is a promising alternative. Some studies in the elderly[26] and children[27] concluded that cystatin-c showed a high correlation with measured GFR in young and older patients with CKD than creatinine. Thus, cystatin-c can be established as a useful alternative marker to creatinine in CKD patients.

A study[28] concluded that estimating GFR using formulae based on creatinine or cystatin-c alone was equally accurate according to the NKF KDOQI guidelines. A formula that combines both provided greater accuracy; our study also showed a similar result. Overall, the patients were correctly classified for the different stages of CKD in 62.1%–64.0% for the creatinine-based equations, 61.5%–72.0% for the cystatin-c-based equations and 70.2%–73.9% for the combination.

A study[29] estimated GFR among persons with type 1 diabetes mellitus with various markers such as creatinine, cystatin c and β2-microglobulin and compared with inulin clearance, found that all equations with the exception of β2-microglobulin have significantly underestimated GFR with cystatin c showing the greatest bias. In the present study, we did not employ an exogenous marker-like inulin clearance, did not include β2-microglobulin based eGFR estimation and included CKD patients; however, our study found equations based on cystatin c better correlating with other eGFR equations.

In the present study, eGFR by EPI-creatinine and cystatin-c equation better correlated with all other equations using creatinine or cystatin-c alone, and the strength of the correlation is significant (more than 0.8). There is a very weak correlation between eGFR calculated by creatinine and eGFR calculated by cystatin-c alone (coefficient 0.4), suggesting a significant difference between creatinine and cystatin-c for the estimation of GFR. Hence, using both creatinine and cystatin-c for the estimation of GFR would be better for confirmation and classifying CKD. We recommend cystatin-c a better alternative for estimation of GFR compared to creatinine as it is not influenced by muscle mass, BMI and dietary intake, especially in the elderly. Out of the four equations for estimation of GFR, EPI-cystatin-c and creatinine equation might be the better equation for confirming and classifying in elderly CKD patients as it has a better correlation with all the other three equations. The outcome of this study is similar to other non-Indian studies showing that GFR calculated with a combined Cystatin-c and Creatinine is superior to cystatin-c or creatinine alone. Further studies in the Indian population are needed to implement the use of cystatin-c in routine clinical practice diagnosing and classifying CKD.

Limitations of the present study include small sample size; GFR was not measured in our study to compare the estimated GFR using different equations.

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Conflicts of interest

There are no conflicts of interest.

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  [Figure 1], [Figure 2]

  [Table 1], [Table 2], [Table 3], [Table 4]


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