• Users Online: 1178
  • Home
  • Print this page
  • Email this page
Home About us Editorial board Search Ahead of print Current issue Archives Submit article Instructions Subscribe Contacts Login 

 Table of Contents  
ORIGINAL ARTICLE
Year : 2015  |  Volume : 40  |  Issue : 4  |  Page : 185-189

The utility of the CKD-EPI formula for determination of glomerular filtration rate in Nigerians with sickle cell disease


1 Department of Haematology, Nnamdi Azikiwe University Teaching Hospital, Nnewi, Nigeria
2 Department of Haematology, Obafemi Awolowo University, Ile-Ife, Nigeria
3 Department of Chemical Pathology, Obafemi Awolowo University, Ile-Ife, Nigeria
4 Department of Medicine, Obafemi Awolowo University, Ile-Ife, Nigeria

Date of Submission23-Jun-2015
Date of Acceptance08-Aug-2015
Date of Web Publication23-Nov-2015

Correspondence Address:
Anthony A Oyekunle
Department of Haematology and Immunology, Obafemi Awolowo University, 234-220005 Ile-Ife, Osun State
Nigeria
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/1110-1067.170217

Rights and Permissions
  Abstract 

Background and objective Predictive formulae for the calculation of estimated glomerular filtration rate (eGFR) are increasingly being used in clinical practice for monitoring of renal function. We evaluated the usefulness of the CKD-EPI formula for eGFR in a population of Nigerian patients with sickle cell disease (SCD).
Patients and methods One hundred SCD patients were prospectively studied. Relevant information, including age, weight and sex, was obtained from the participants, whereas creatinine clearance was measured following a 24-h urine collection. The Cockcroft-Gault (C-G) and the CKD-EPI formulae were thereafter used to calculate the glomerular filtration rate (GFR) for all participants. SPSS (version 17) and Microsoft Excel 2007 computer software were used for all data collection and analyses. A P-value of less than 0.05 was considered significant.
Results The comparison of measured GFR versus eGFR by the C-G and CKD-EPI formulae in homozygous haemoglobin SS (HbSS) patients yielded correlation coefficients (r values) of 0.667 (P < 0.001) and 0.598 (P < 0.001), respectively. Correspondingly, among the heterozygous haemoglobin S + C (HbSC) patients, measured GFR versus eGFR resulted in r values of 0.819 (P < 0.001) and 0.848 (P < 0.001), respectively.
Conclusion The CKD-EPI formula is a good measure of eGFR in our population of SCD patients; however, it did not perform significantly better than the C-G formula.

Keywords: chronic kidney disease , CKD-EPI , estimated glomerular filtration rate, sickle cell disease


How to cite this article:
Aneke JC, Oyekunle AA, Adegoke AO, Sanusi AA, Okocha EC, Akinola NO, Durosinmi MA. The utility of the CKD-EPI formula for determination of glomerular filtration rate in Nigerians with sickle cell disease. Egypt J Haematol 2015;40:185-9

How to cite this URL:
Aneke JC, Oyekunle AA, Adegoke AO, Sanusi AA, Okocha EC, Akinola NO, Durosinmi MA. The utility of the CKD-EPI formula for determination of glomerular filtration rate in Nigerians with sickle cell disease. Egypt J Haematol [serial online] 2015 [cited 2020 Jan 19];40:185-9. Available from: http://www.ehj.eg.net/text.asp?2015/40/4/185/170217


  Introduction Top


Assessment of renal function is an integral component of the comprehensive care of patients with sickle cell disease (SCD). This is made even more important by the finding that renal dysfunction is a major determinant of survival in SCD [1] . Kidney dysfunction, with potential for progression to end-stage kidney disease, is a major contributor to the morbidity and mortality of patients with SCD [2],[3] . In fact, end-stage kidney disease has variously been documented in up to 11% of these patients [4],[5] . In monitoring for sickle cell nephropathy, evaluation of proteinuria is important as it has been shown to indicate early glomerular dysfunction. This makes it an important marker of kidney pathology [2] .

Glomerular filtration rate (GFR) is usually determined by measuring the creatinine clearance after a 24-h urine collection. This is time-consuming and laborious and cannot be easily measured in clinical practice. Consequently, predictive formulae have been developed to enable easier and faster calculation of GFR utilizing parameters such as serum creatinine, body size, age, race and sex [6],[7] . A number of predictive formulae are currently available that enable the determination of estimated glomerular filtration rate (eGFR) in different disease states with reasonable degrees of accuracy and precision. The Cockcroft-Gault (C-G) [8] formula has gained widespread acceptance and has equally been variously validated in cardiac [9] , renal [10] and recently in our population of SCD [11] patients.

Methods of GFR determination based on creatinine clearance are limited by the observation of renal tubular dysfunction in SCD, which leads to increased tubular secretion of creatinine and the consequent overestimation of GFR [12] . Indeed, Haymann et al. [13] reported some overestimation of true GFR when comparing the eGFR using the four-variable modification of diet in renal disease (MDRD) formula with 51 Cr-EDTA-based measured GFR, despite a good correlation. Moreover, Aparicio et al. [14] noted that a reduction in creatinine generation because of decreased muscle mass and changes in protein catabolism and hydration in SCD affects the results of creatinine clearance and also reported a poor correlation between measured GFR using 51 Cr-EDTA and values using creatinine clearance. Similarly, studies in children with SCD have shown a poor correlation between measured GFR by the 99m Tc-DTPA method and those utilizing urinary clearance of creatinine and cystatin C [15] . However, the use of radioisotopes for routine clinical assessment of GFR is yet to receive wide acceptance because they are largely labour intensive and hazardous [16] .

The shortcomings of creatinine-based methods of GFR estimation notwithstanding, they are still used widely on account of their convenience and safety. A number of studies have alluded to the accuracy, precision and clinical adequacy of the predictive formulae derived from GFR measurements in different disease states [9],[10],[11] . The unique pathophysiologic changes associated with sickle cell nephropathy have made it necessary that a disease-specific formula be developed for patients with this condition [17],[18] . The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) research group recently introduced a new equation [19] , which has been validated independently by several research groups [20],[21],[22] .

This study evaluated the performance of the CKD-EPI formula for eGFR in Nigerian patients with SCD.


  Patients and methods Top


The study was prospective, carried out over a 7-month period from January to July 2010. Ethical approval was obtained from the Hospital Ethics Committee and all participants provided informed consent; consent was provided by the parent or the guardian for patients younger than 18 years old. Patients were between 15 and 56 years of age, and were regular attendees of the Hematology Outpatient Clinic of our hospital; there were 100 confirmed (by cellulose acetate electrophoresis, at alkaline pH) patients with SCD [79 homozygous sickle cell anaemia (HbSS) and 21 compound heterozygous sickle cell disease (HbSC) patients, mainly from south-west Nigeria] in stable clinical conditions at least 2 weeks before recruitment and had not received blood transfusion in the last 3 months. Exclusion criteria included oedema or ketosis (which may be indicative of congestive cardiac failure or complicated diabetes mellitus) and those currently on drugs such as co-trimoxazole, probenecid or cephalosporins, which are known to interfere with the tubular excretion of creatinine and alkaline picrate assay (Jaffé reaction) for serum creatinine [23] .

Relevant clinical information was documented, and a 24-h urine collection was performed for each participant on an outpatient basis, using wide-bore 4-l containers to which boric acid had been added. On the morning of submission of the 24-h urine sample, 2.5 ml of venous blood was collected for serum creatinine estimation. Each participant was adequately and extensively counselled before commencement of urine collection to avoid errors. Both urinary and serum creatinine estimations were performed using Jaffe's reaction [24] . The eGFR calculations were performed using the following formulae: C-G [8] : [(140−age) × (weight, kg) × (0.85, if female)]/(72 × SCr) and CKD-EPI [19] : 141 × min(SCr/κ, 1)α × max(SCr/κ, 1)−1.209 × 0.993 age × 1.018 (if female) × 1.159 (if Black), where SCr is the serum creatinine (mg/dl), κ is 0.7 (female) or 0.9 (male), a is −0.329 (female) or −0.411 (male), min is the minimum of SCr/κ and 1 and max is the maximum of SCr/κ and 1. The measured and eGFR were both adjusted for body surface area (1.73 m 2 ), calculated using the Mosteller formula [25] : [height (cm) × weight (kg)/3600] 0.5 . SPSS (version 17; SPSS Inc., Chicago, Illinois, USA) and Microsoft Excel (2007) computer software were used for data collection and analysis. Pair-wise correlations were performed between measured and eGFR estimated using the two formulae. A P-value less than 0.05 was considered significant.


  Results Top


The patients (HbSS, n = 79; HbSC, n = 21) included 40 males and 60 females. The mean age of the HbSS and HbSC patients was 25.34 ± 6.77 years (range, 15-56 years) and 29.33 ± 8.97 years (range, 17-50 years), respectively.

The means of measured GFR in HbSS and HbSC were 66.28 ± 27.52 and 97.04 ± 17.47 ml/min/1.73 m 2 , respectively. Correspondingly, the mean eGFR were 56.26 ± 15.03 and 57.55 ± 17.46 ml/min/1.73 m 2 using the C-G formula and 115.44 ± 28.98 and 108.78 ± 30.78 ml/min/1.73 m 2 using the CKD-EPI formula in HbSS and HbSC, respectively ([Table 1]). Using the Kidney Disease: Improving Global Outcomes (KDIGO) classification [26] , the majority of the patients (75 and 62% HbSS and HbSC, respectively) had 'normal or high' kidney function ([Table 2]).
Table 1: Means and standard deviations of measured and calculated GFR in HbSS and HbSC


Click here to view
Table 2: The distribution of estimated GFR of subjects using the KDIGO 2012* nomenclature


Click here to view


Among the HbSS patients, measured GFR correlated significantly with the eGFR obtained by the C-G (r = 0.667, P < 0.001) and the CKD-EPI formulae (r = 0.598, P < 0.001). There was a better correlation between the measured GFR and the eGFR of the HbSC patients both by the C-G (r = 0.819, P < 0.001) and by the CKD-EPI formulae (r = 0.848, P < 0.001). shows the detailed comparisons between measured GFR and eGFR of the patients ([Table 3]).
Table 3: Correlation of Measured and calculated GFR in HbSS and HbSC


Click here to view


Using a Bland-Altman analysis, there was a mean overestimation of GFR by 49.17 ± 25.36 and 35.03 ± 20.65 ml/min in the HbSS and HbSC patients, respectively, using the CKD-EPI formula, whereas correspondingly, the C-G was underestimated by a mean of 10.02 ± 21.17 and 11.83 ± 13.31 ml/min ([Figure 1]).
Figure 1 Bland-Altman analysis of measured versus estimated glomerular filtration rate (eGFR) using CKD-EPI and Cockcroft-Gault (C-G) formulae. The Bland-Altman plots for heterozygous haemoglobin SC (b, d) and homozygous haemoglobin SS (a, c) show overestimation of the measured GFR by the CKD-EPI formula (a, b), whereas the C-G formula underestimates the measured GFR (c, d).

Click here to view



  Discussion Top


We had previously evaluated the utility of five predictive formulae for eGFR in our SCD patients, including the C-G, MDRD, Mawer, Gates and Hull. It was observed that eGFR by the C-G formula correlated best with measured GFR (using creatinine clearance) [11] . Similarly, several studies have also reported high correlations between the C-G formula and measured GFR in Nigerian patients with hypertension, congestive heart failure and chronic renal failure [9],[10] .

Following the introduction of the CKD-EPI formula, it has been shown to be a useful predictor of GFR in lean patients of sub-Saharan African descent [20] . It thus became imperative that this 'new' formula be tested in adult non-European, non-American SCD patients. Arlet et al. [21] reported eGFR by the CKD-EPI formula (in SCD patients aged between 18 and 67.5 years) as having the best correlation with measured GFR using the iohexol plasma clearance method, and thus recommended it be used for eGFR in SCD patients of non-Afro-American origin [21] . Similarly, Asnani et al. [22] compared eGFR derived from CKD-EPI, the C-G and the MDRD formulae with measured GFR using a 99m Tc-DTPA nuclear renal scan in a cohort of Jamaican sickle cell anaemia patients. They observed that eGFR based on the CKD-EPI formula showed a better correlation with measured GFR.

Our study showed that the CKD-EPI formula consistently overestimated GFR in HbSS and HbSC patients by an average of 49.19 and 11.7 ml/min, respectively. Interestingly, GFR overestimation was less in HbSC than in HbSS patients. Asnani et al. [22] had similarly noted GFR overestimation in HbSS patients using the CKD-EPI formula by a mean of 41.2 ml/min. In our HbSS patients, both formulae correlated significantly with measured creatinine clearance, even though the C-G formula performed better (r = 0.667 vs. 0.598). Similarly, both formulae correlated significantly with measured creatinine clearance in our HbSC patients, although the CKD-EPI formula seemed to be better (r = 0.848 vs. 0.819).

Our finding in HbSS patients is in contrast with the reports of Arlet et al. [21] and Asnani et al. [22] , both of which alluded to the superiority of the CKD-EPI formula in SCD patients. Although this discrepancy may reflect a true difference in patient populations as our patients were mainly from the Yoruba tribe of south-west Nigeria, the patients in the two studies alluded to above were mainly from the Caribbean. An increasing body of evidence has identified tribal (because of genetics) differences in GFR in health and disease [27],[28],[29] . In addition, it is important to note that different reference methods of GFR measurement were also used in these studies. Evaluation of tribal differences in GFR (and possibly its genetic determinants) among Nigerian patients could therefore be a subject of further research.

In conclusion, our study confirms that the CKD-EPI formula offers a good measure of GFR estimation in Nigerian SCD patients, although it slightly overestimates GFR measured by creatinine clearance. In addition, the CKD-EPI did not perform significantly better than the C-G formula in our cohort of patients. Some limitations of this study include the fact that reference markers such as inulin, 125 I-iothalamate, iohexol, technetium, diethylene triaminepentaacetic acid and chromium ethylene diaminetetraacetic acid, which are known to be superior to creatinine clearance, could not be used for GFR determination because of lack of facilities for them locally. Similarly, the diagnosis of SCD using haemoglobin electrophoresis alone could fail to detect patients with concurrent α-thalassaemia.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

 
  References Top

1.
Platt OS, Brambilla DJ, Rosse WF, Milner PF, Castro O, Steinberg MH, Klug PP. Mortality in sickle cell disease. Life expectancy and risk factors for early death. N Engl J Med 1994; 330 :1639-1644.  Back to cited text no. 1
    
2.
Abdu A, Emokpae MA, Uadia PO, Kuliya-Gwarzo A. Proteinuria among adult sickle cell anemia patients in Nigeria. Ann Afr Med 2011; 10 :34-37.  Back to cited text no. 2
    
3.
López Revuelta K, Ricard Andrés MP. Kidney abnormalities in sickle cell disease. Nefrologia 2011; 31 :591-601.  Back to cited text no. 3
    
4.
Powars DR, Elliott-Mills DD, Chan L, Niland J, Hiti AL, Opas LM, Johnson C. Chronic renal failure in sickle cell disease: risk factors, clinical course, and mortality. Ann Intern Med 1991; 115 :614-620.  Back to cited text no. 4
    
5.
Serjeant GR, Higgs DR, Hambleton IR. Elderly survivors with homozygous sickle cell disease. N Engl J Med 2007; 356 :642-643.  Back to cited text no. 5
[PUBMED]    
6.
Kopple JD. National kidney foundation K/DOQI clinical practice guidelines for nutrition in chronic renal failure. Am J Kidney Dis 2001; 37 :S66-S70.  Back to cited text no. 6
    
7.
Stevens LA, Coresh J, Greene T, Levey AS. Assessing kidney function - measured and estimated glomerular filtration rate. N Engl J Med 2006; 354 :2473-2483.  Back to cited text no. 7
    
8.
Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron 1976; 16 :31-41.  Back to cited text no. 8
[PUBMED]    
9.
Ajayi AA. Estimation of creatinine clearance from serum creatinine: utility of the Cockroft and Gault equation in Nigerian patients. Eur J Clin Pharmacol. 1991; 40 :429-431.  Back to cited text no. 9
    
10.
Sanusi AA, Akinsola A, Ajayi AA. Creatinine clearance estimation from serum creatinine values: evaluation and comparison of five prediction formulae in Nigerian patients. Afr J Med Med Sci 2000; 29 :7-11.  Back to cited text no. 10
    
11.
Adegoke AO, Aneke JC, Oyekunle AA, Nouraie SM, Sanusu AA, Akinola NO, Durosinmi MA. Evaluation of the performance of predictive formulae in the assessment of glomerular filtration rate in patients with sickle cell disease. Ann Trop Pathol. 2012; 3 :9-15.  Back to cited text no. 11
    
12.
Thompson J, Reid M, Hambleton I, Serjeant GR. Albuminuria and renal function in homozygous sickle cell disease: observations from a cohort study. Arch Intern Med 2007; 167 :701-708.  Back to cited text no. 12
    
13.
Haymann JP, Stankovic K, Levy P, Avellino V, Tharaux PL, Letavernier E, et al. Glomerular hyperfiltration in adult sickle cell anemia: a frequent hemolysis associated feature. Clin J Am Soc Nephrol 2010; 5 :756-761.  Back to cited text no. 13
    
14.
Aparicio SA, Mojiminiyi S, Kay JD, Shepstone BJ, de Ceulaer K, Serjeant GR. Measurement of glomerular filtration rate in homozygous sickle cell disease: a comparison of 51 Cr-EDTA clearance, creatinine clearance, serum creatinine and beta 2 microglobulin. J Clin Pathol 1990; 43 :370-372.  Back to cited text no. 14
    
15.
Aygun B, Mortier NA, Smeltzer MP, Hankins JS, Ware RE. Glomerular hyperfiltration and albuminuria in children with sickle cell anemia. Pediatr Nephrol 2011; 26 :1285-1290.  Back to cited text no. 15
    
16.
Itoh K. Determination of glomerular filtration rate by means of newly developed plastic scintillation counter both with and without dilution procedures. J Nucl Med 2001; 42 :1484-1488.  Back to cited text no. 16
    
17.
Phuong-Thu TP, Phuong-Chi TP, Alan HW, Susie QL. Renal abnormalities in sickle cell disease. Kidney Int 2000; 57 :1-8.  Back to cited text no. 17
    
18.
Walker BR, Alexander F, Birdsall TR, Warren RL. Glomerular lesions in sickle cell nephropathy. JAMA 1971; 215 :437-440.  Back to cited text no. 18
[PUBMED]    
19.
Levey AS, Coresh J, Balk E, Kausz AT, Levin A, Steffes MW, et al., National Kidney Foundation National Kidney Foundation practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Ann Intern Med 2003; 139 :137-147.  Back to cited text no. 19
    
20.
Eastwood JB, Kerry SM, Plange-Rhule J, Micah FB, Antwi S, Boa FG, et al. Assessment of GFR by four methods in adults in Ashanti, Ghana: the need for an eGFR equation for lean African populations. Nephrol Dial Transplant 2010; 25 :2178-2187.  Back to cited text no. 20
    
21.
Arlet JB, Ribeil JA, Chatellier G, Eladari D, De Seigneux S, Souberbielle JC, et al. Determination of the best method to estimate glomerular filtration rate from serum creatinine in adult patients with sickle cell disease: a prospective observational cohort study. BMC Nephrol 2012; 13 :83.  Back to cited text no. 21
    
22.
Asnani MR, Lynch O, Reid ME. Determining glomerular filtration rate in homozygous sickle cell disease: utility of serum creatinine based estimating equations. PLoS One 2013; 8 :e69922.  Back to cited text no. 22
    
23.
Lascano ME, Poggio ED. Kidney function assessment by creatinine-based estimation equations. Kidney 2010; 2 :58.  Back to cited text no. 23
    
24.
Burtis CA, Ashwood ER. Tietz fundamentals of clinical chemistry. Philadelphia: W.B. Saunders Company; 2001.  Back to cited text no. 24
    
25.
Mosteller RD. Simplified calculation of body-surface area. N Engl J Med 1987; 317 :1098.  Back to cited text no. 25
[PUBMED]    
26.
Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group. KDIGO 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease. Kidney inter., Suppl. 2013; 3 : 1-150.  Back to cited text no. 26
    
27.
Fox CS, Yang Q, Cupples LA, Guo CY, Larson MG, Leip EP, et al. Genomewide linkage analysis to serum creatinine, GFR, and creatinine clearance in a community-based population: the Framingham Heart Study. J Am Soc Nephrol 2004; 15 :2457-2461.  Back to cited text no. 27
    
28.
28. Hunter DJ, Lange Md, Snieder H, MacGregor AJ, Swaminathan R, Thakker RV, Spector TD Genetic contribution to renal function and electrolyte balance: a twin study. Clin Sci (Lond) 2002; 103 :259-265  Back to cited text no. 28
    
29.
Bathum L, Fagnani C, Christiansen L, Christensen K. Heritability of biochemical kidney markers and relation to survival in the elderly - results from a Danish population-based twin study. Clin Chim Acta 2004; 349 :143-150.  Back to cited text no. 29
    


    Figures

  [Figure 1]
 
 
    Tables

  [Table 1], [Table 2], [Table 3]



 

Top
 
 
  Search
 
Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

 
  In this article
Abstract
Introduction
Patients and methods
Results
Discussion
References
Article Figures
Article Tables

 Article Access Statistics
    Viewed1116    
    Printed17    
    Emailed0    
    PDF Downloaded153    
    Comments [Add]    

Recommend this journal


[TAG2]
[TAG3]
[TAG4]