EVALUATION OF GLOMERULAR FILTRATION RATE ESTIMATING EQUATIONS IN CKD PATIENTS WITH DIABETES AND HYPERTENSION

Authors

  • GANESH SRITHERAN PANEERSELVAM School of Pharmacy, Taylors University, 47500 Subang Jaya, Selangor
  • YAMAN WALID KASSAB Faculty of Pharmacy, Cyberjaya University College of Medical Sciences, 63000 Cyberjaya, Selangor, Malaysia

DOI:

https://doi.org/10.22159/ijpps.2020v12i4.37120

Keywords:

Chronic kidney disease, Estimated glomerular filtration rate, Cockcroft-Gault, Modification of diet in renal disease

Abstract

Objective: To compare the performance of Cockcroft-Gault and Modification of Diet in Renal Disease (MDRD) equations in estimating kidney function in CKD patients with diabetes and hypertension.

Methods: This study retrospectively reviewed medical records in Hospital Kajang. The GFR was calculated using Cockcroft-Gault and MDRD equations. Kappa Measure of Agreement was used to check the consistency of CKD staging. Wilcoxon signed-ranked tests and Bland-Altman plots were used to determine the difference of both equations. Spearman correlation was used to determine the correlation between blood pressure and blood sugar levels with eGFR.

Results: Data pertaining to a total of 81 patients were extracted. Results showed 22% of the patients were staged differently (Kappa value = 0.644 [P<0.001]) and the majority of them moved down one CKD stage when MDRD equation was used instead of Cockcroft-Gault equation. Wilcoxon signed rank test demonstrated there was a significant difference (P<0.001) in eGFR using CandG and MDRD in patients with diabetes and hypertension. Furthermore, the mean difference observed was 3.78±5.56 [P<0.001]), where the Cockcroft-Gault equation measured 3.78 units higher than MDRD equation. However, the relationship between blood sugar and blood pressure with eGFR were not significant.

Conclusion: There was a significant difference between Cockcroft-Gault and MDRD equations in estimating kidney function CKD patients with diabetes and hypertension.

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References

Bikbov B, Perico N, Remuzzi G. Mortality landscape in the global burden of diseases, injuries and risk factors study. Eur J Intern Med 2014;25:1–5.

Hooi LS, Ong LM, Ahmad G, Bavanandan. A population-based study measuring the prevalence of chronic kidney disease among adults in West Malaysia. Kidney Int 2013;84:1034–40.

Ayodele OE, Alebiosu CO. Burden of chronic kidney disease: an international perspective. Adv Chronic Kidney Dis 2010;17:215–24.

Jha V, Garcia Garcia G, Iseki K, Li Z, Naicker S, Plattner B, et al. Chronic kidney disease: global dimension and perspectives. Lancet 2013;382:260–72.

Levey AS, Coresh J. Chronic kidney disease. Lancet 2012;379:165–80.

Ministry of Health Malaysia. Laboratory Investigation Guidelines For Chronic Kidney Disease and Utilisation of eGFR in adult; 2012.

Botev R, Mallie JP, Couchoud C. Estimating glomerular filtration rate: cockcroft-gault and modification of diet in renal disease formulas compared to renal inulin clearance. Clin J Am Soc Nephrol 2009;4:899–906.

Chauvelier S, Pequignot R, Amzal A, Hanon O, Belmin J. Comparison between the three most popular formulae to estimate renal function, in subjects 75 y of age or older. Drugs Aging 2012;29:885–90.

Hsu CY, Bansal N. Measured GFR as “gold standard”-All that glitters is not gold? CJASN 2011;6:1813–4.

Almualm Y, Huri HZ. Chronic kidney disease screening methods and its implication for malaysia: an in depth review. Glob J Health Sci 2015;7:96–109.

Froissart M, Rossert J, Jacquot C, Paillard M, Houillier P. Predictive performance of the modification of diet in renal disease and cockcroft-gault equations for estimating renal function. JASN 2005;16:763–73.

Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron 1976;16:31–41.

Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med 1999;130:461–70.

Levin A, Stevens PE, Bilous RW, Coresh J, De Francisco ALM, De Jong PE, et al. Kidney disease: improving global outcomes (KDIGO) CKD work group. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int Suppl 2013;3:1-150.

Helou R. Should we continue to use the cockcroft-gault formula? Nephron Clin Pract 2010;116:172–86.

Trinkley KE, Nikels SM, Ii RLP, Joy MS. Automating and estimating glomerular filtration rate for dosing medications and staging chronic kidney disease. Int J Gen Med 2014;7:211–8.

Ali A, Asif N, Rais Z. Estimation of GFR by MDRD formula and Its correlation to the cockcroft-gault equation in five stages of chronic kidney disease. Open J Nephrol 2013;3:37–40.

Dehghani H, Heidari F, Mozaffari khosravi H, Nouri Majelan N, Rahmanian M, Dehghani A. Evaluation of glomerular filtration rate estimating formulas in diabetic patients with chronic kidney disease. Iran J Diabetes Obes 2013;5:47–53.

Poggio ED, Wang X, Greene T, Van Lente F, Hall PM. Performance of the modification of diet in renal disease and cockcroft-gault equations in the estimation of GFR in health and in chronic kidney disease. J Am Soc Nephrol 2005;16:459–66.

Rigalleau V, Lasseur C, Perlemoline C, Barthe N, Raffaitin C, Liu C, et al. Estimation of glomerular filtration rate in diabetic subjects: cockcroft formula or modification of diet-disease study equation? Diabetes Care 2005:28:838-43.

Rigalleau V, Beauvieux MC, Gonzalez C, Raffaitin C, Lasseur C, Combe C, et al. Estimation of renal function in patients with diabetes. Diabetes Metab 2011;37:359–66.

Published

01-04-2020

How to Cite

PANEERSELVAM, G. S. ., and Y. W. . KASSAB. “EVALUATION OF GLOMERULAR FILTRATION RATE ESTIMATING EQUATIONS IN CKD PATIENTS WITH DIABETES AND HYPERTENSION”. International Journal of Pharmacy and Pharmaceutical Sciences, vol. 12, no. 4, Apr. 2020, pp. 49-52, doi:10.22159/ijpps.2020v12i4.37120.

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Original Article(s)