CLINICAL PRACTICE BASE EGFR EQUATIONS AND THEIR APPLICATIONS IN DIFFERENT CKD POPULATIONS: A NARRATIVE REVIEW
Main Article Content
Keywords
Cystatin C, Creatinine, endogenous biomarker, kidney, chronic kidney disease
Abstract
Every generation of medical students has learned the Cockcroft–Gault equation, which estimates the glomerular filtration rate. However, since the Modification of Diet in Renal Disease (MDRD) study equation was published in 1999, the superiority of the Cockcroft–Gault equation has been consistently debated. Recently, the Chronic Kidney Disease Epidemiology (CKD-EPI) consortium introduced a set of innovative equations for estimating the glomerular filtration rate (GFR). The MDRD and CKD-EPI equations were developed through a rigorous process, are formulated to work with standardized biomarkers of GFR (such as serum creatinine and/or serum cystatin C) and have been evaluated in various patient populations. The MDRD Study and CKD-EPI equation based on serum creatinine level have replaced the Cockcroft–Gault equation. These equations are generally considered superior and are specifically recommended by international guidelines. However, as they become more widely used, it has become evident that they are not infallible and may not provide accurate GFR estimates in certain everyday clinical situations. This review describes the development processes of the new GFR-estimating equations, and the clinical scenarios in which their applicability is questioned are discussed
References
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6. Rehberg, P.B., Studies on kidney function: the rate of filtration and reabsorption in the human kidney. Biochemical Journal, 1926. 20(3): p. 447.
7. Heymsfield, S.B., et al., Measurement of muscle mass in humans: validity of the 24-hour urinary creatinine method. The American journal of clinical nutrition, 1983. 37(3): p. 478-494.
8. Mayersohn, M., K.A. Conrad, and R. Achari, The influence of a cooked meat meal on creatinine plasma concentration and creatinine clearance. British journal of clinical pharmacology, 1983. 15(2): p. 227-230.
9. Clausen, J., Proteins in normal cerebrospinal fluid not found in serum. Proceedings of the Society for Experimental Biology and Medicine, 1961. 107(1): p. 170-172.
10. Abrahamson, M., et al., Structure and expression of the human cystatin C gene. Biochemical journal, 1990. 268(2): p. 287-294.
11. Tenstad, O., et al., Renal handling of radiolabelled human cystatin C in the rat. Scandinavian journal of clinical and laboratory investigation, 1996. 56(5): p. 409-414.
12. Grubb, A., et al., Serum concentration of cystatin C, factor D and β2‐microglobulin as a measure of glomerular filtration rate. Acta Medica Scandinavica, 1985. 218(5): p. 499-503.
13. Stevens, L.A., et al., Factors other than glomerular filtration rate affect serum cystatin C levels. Kidney international, 2009. 75(6): p. 652-660.
14. Galteau, M.-M., et al., Determination of serum cystatin C: biological variation and reference values. 2001.
15. Fricker, M., et al., Impact of thyroid dysfunction on serum cystatin C. Kidney international, 2003. 63(5): p. 1944-1947.
16. Gagneux-Brunon, A., C. Mariat, and P. Delanaye, Cystatin C in HIV-infected patients: promising but not yet ready for prime time. Nephrology Dialysis Transplantation, 2012. 27(4): p. 1305-1313.
17. Segarra, A., et al., Assessing glomerular filtration rate in hospitalized patients: a comparison between CKD-EPI and four cystatin C-based equations. Clinical Journal of the American Society of Nephrology: CJASN, 2011. 6(10): p. 2411.
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19. EFFERSØE, P., Relationship between endogenous 24‐hour creatinine clearance and serum creatinine concentration in patients with chronic renal disease. Acta Medica Scandinavica, 1957. 156(6): p. 429-434.
20. Cockcroft, D.W. and H. Gault, Prediction of creatinine clearance from serum creatinine. Nephron, 1976. 16(1): p. 31-41.
21. Levey, A.S., et al., A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Annals of internal medicine, 1999. 130(6): p. 461-470.
22. Delanaye, P. and J.-M. Krzesinski, Indexing of renal function parameters by body surface area: intelligence or folly? Nephron Clinical practice, 2011. 119(4): p. c289-c292.
23. Millar, J.A., The Cockroft and Gault formula for estimation of creatinine clearance: a friendly deconstruction. The New Zealand Medical Journal (Online), 2012. 125(1350).
24. Eriksen, B.O., et al., GFR normalized to total body water allows comparisons across genders and body sizes. Journal of the American Society of Nephrology: JASN, 2011. 22(8): p. 1517.
25. Nyman, H.A., et al., Comparative evaluation of the Cockcroft‐Gault Equation and the Modification of Diet in Renal Disease (MDRD) study equation for drug dosing: an opinion of the Nephrology Practice and Research Network of the American College of Clinical Pharmacy. Pharmacotherapy: The Journal of Human Pharmacology and Drug Therapy, 2011. 31(11): p. 1130-1144.
26. Macisaac, R.J., et al., Estimating glomerular filtration rate in diabetes: a comparison of cystatin-C-and creatinine-based methods. Diabetologia, 2006. 49: p. 1686-1689.
27. Rule, A.D., et al., Using serum creatinine to estimate glomerular filtration rate: accuracy in good health and in chronic kidney disease. Annals of internal medicine, 2004. 141(12): p. 929-937.
28. Murthy, K., et al., Variation in the serum creatinine assay calibration: a practical application to glomerular filtration rate estimation. Kidney international, 2005. 68(4): p. 1884-1887.
29. Schwartz, G.J., et al., Improved equations estimating GFR in children with chronic kidney disease using an immunonephelometric determination of cystatin C. Kidney international, 2012. 82(4): p. 445-453.
30. Levey, A.S., et al., A new equation to estimate glomerular filtration rate. Annals of internal medicine, 2009. 150(9): p. 604-612.
31. Delanaye, P., et al., MDRD or CKD-EPI study equations for estimating prevalence of stage 3 CKD in epidemiological studies: which difference? Is this difference relevant? BMC nephrology, 2010. 11: p. 1-7.
32. Matsushita, K., et al., Risk implications of the new CKD Epidemiology Collaboration (CKD-EPI) equation compared with the MDRD Study equation for estimated GFR: the Atherosclerosis Risk in Communities (ARIC) Study. American journal of kidney diseases, 2010. 55(4): p. 648-659.
33. White, S.L., et al., Comparison of the prevalence and mortality risk of CKD in Australia using the CKD Epidemiology Collaboration (CKD-EPI) and Modification of Diet in Renal Disease (MDRD) Study GFR estimating equations: the AusDiab (Australian Diabetes, Obesity and Lifestyle) Study. American journal of kidney diseases, 2010. 55(4): p. 660-670.
34. Murata, K., et al., Relative performance of the MDRD and CKD-EPI equations for estimating glomerular filtration rate among patients with varied clinical presentations. Clinical journal of the American Society of Nephrology: CJASN, 2011. 6(8): p. 1963.
35. Björk, J., et al., Validation of the Lund–Malmö, Chronic Kidney Disease Epidemiology (CKD-EPI) and Modification of Diet in Renal Disease (MDRD) equations to estimate glomerular filtration rate in a large Swedish clinical population. Scandinavian journal of urology and nephrology, 2012. 46(3): p. 212-222.
36. Buron, F., et al., Estimating glomerular filtration rate in kidney transplant recipients: performance over time of four creatinine-based formulas. Transplantation, 2011. 92(9): p. 1005-1011.
37. Bargnoux, A., et al., Accuracy of GFR predictive equations in renal transplantation: Validation of a new turbidimetric cystatin C assay on Architect c8000®. Clinical biochemistry, 2012. 45(1-2): p. 151-153.
38. White, C.A., et al., Estimating glomerular filtration rate in kidney transplantation: is the new chronic kidney disease epidemiology collaboration equation any better? Clinical chemistry, 2010. 56(3): p. 474-477.
39. Stevens, L.A., et al., Comparative performance of the CKD Epidemiology Collaboration (CKD-EPI) and the Modification of Diet in Renal Disease (MDRD) Study equations for estimating GFR levels above 60 mL/min/1.73 m2. American Journal of Kidney Diseases, 2010. 56(3): p. 486-495.
40. Harman, G., et al., Accuracy of cystatin C-based estimates of glomerular filtration rate in kidney transplant recipients: a systematic review. Nephrology Dialysis Transplantation, 2013. 28(3): p. 741-757.
41. Masson, I., et al., GFR estimation using standardized cystatin C in kidney transplant recipients. American journal of kidney diseases, 2013. 61(2): p. 279-284.
42. Delanaye, P., et al., Normal reference values for glomerular filtration rate: what do we really know? Nephrology Dialysis Transplantation, 2012. 27(7): p. 2664-2672.
43. Van Den Noortgate, N.J., et al., Serum cystatin C concentration compared with other markers of glomerular filtration rate in the old old. Journal of the American Geriatrics Society, 2002. 50(7): p. 1278-1282.
44. Flamant, M., et al., GFR estimation using the Cockcroft-Gault, MDRD study, and CKD-EPI equations in the elderly. American journal of kidney diseases, 2012. 60(5): p. 847-849.
45. Kilbride, H.S., et al., Accuracy of the MDRD (Modification of Diet in Renal Disease) study and CKD-EPI (CKD Epidemiology Collaboration) equations for estimation of GFR in the elderly. American Journal of Kidney Diseases, 2013. 61(1): p. 57-66.
46. Parveen, S., et al., Prevalence of MRSA colonization among healthcare-workers and effectiveness of decolonization regimen in ICU of a Tertiary care Hospital, Lahore, Pakistan. Advancements in Life Sciences, 2020. 8(1): p. 38-41.
47. Sohail, M., et al., Molecular Characterization of Community-and Hospital-Acquired Methicillin-Resistant Staphylococcus aureus Isolates during COVID-19 Pandemic. Antibiotics, 2023. 12(1): p. 157.
48. Ahmed, N., et al., Antibiotic resistance profile in relation to virulence genes fimH, hlyA and usp of uropathogenic E. coli isolates in Lahore, Pakistan. Trop. Biomed, 2019. 36: p. 559-568.
49. Poggio, E.D., et al., Performance of the Cockcroft-Gault and modification of diet in renal disease equations in estimating GFR in ill hospitalized patients. American journal of kidney diseases, 2005. 46(2): p. 242-252.
50. Delanaye, P., et al., Cystatin C or creatinine for detection of stage 3 chronic kidney disease in anorexia nervosa. Nephron Clinical Practice, 2008. 110(3): p. c158-c163.
51. Xirouchakis, E., et al., Comparison of cystatin C and creatinine-based glomerular filtration rate formulas with 51Cr-EDTA clearance in patients with cirrhosis. Clinical journal of the American Society of Nephrology: CJASN, 2011. 6(1): p. 84.
52. Grootendorst, D.C., et al., The MDRD formula does not reflect GFR in ESRD patients. Nephrology dialysis transplantation, 2011. 26(6): p. 1932-1937.
53. Carrie, B.J., et al., Creatinine: an inadequate filtration marker in glomerular diseases. The American journal of medicine, 1980. 69(2): p. 177-182.
54. Branten, A.J., G. Vervoort, and J.F. Wetzels, Serum creatinine is a poor marker of GFR in nephrotic syndrome. Nephrology Dialysis Transplantation, 2005. 20(4): p. 707-711.
55. Delanghe, J.R., How to estimate GFR in children. Nephrology Dialysis Transplantation, 2009. 24(3): p. 714-716.
56. Finney, H., et al., Reference ranges for plasma cystatin C and creatinine measurements in premature infants, neonates, and older children. Archives of disease in childhood, 2000. 82(1): p. 71-75.
57. Schwartz, G.J., et al., New equations to estimate GFR in children with CKD. Journal of the American Society of Nephrology: JASN, 2009. 20(3): p. 629.
58. Ebert, N., et al., Assessment of kidney function: clinical indications for measured GFR. Clinical kidney journal, 2021. 14(8): p. 1861-1870.
59. Goldwasser, P., A. Aboul-Magd, and M. Maru, Race and creatinine excretion in chronic renal insufficiency. American journal of kidney diseases, 1997. 30(1): p. 16-22.
60. Lewis, J., et al., Comparison of cross-sectional renal function measurements in African Americans with hypertensive nephrosclerosis and of primary formulas to estimate glomerular filtration rate. American journal of kidney diseases, 2001. 38(4): p. 744-753.
61. Delanaye, P., et al., Are the creatinine-based equations accurate to estimate glomerular filtration rate in African American populations? Clinical Journal of the American Society of Nephrology, 2011. 6(4): p. 906-912.
62. van Deventer, H.E., et al., A comparison of cystatin C-and creatinine-based prediction equations for the estimation of glomerular filtration rate in black South Africans. Nephrology Dialysis Transplantation, 2011. 26(5): p. 1553-1558.
63. Maple-Brown, L.J., et al., Accurate assessment of kidney function in indigenous Australians: the estimated GFR study. American Journal of Kidney Diseases, 2012. 60(4): p. 680-682.
64. Delanaye, P., et al., Estimating glomerular filtration rate in Asian subjects: where do we stand? Kidney international, 2011. 80(5): p. 439-440.
65. Teo, B.W., et al., GFR estimating equations in a multiethnic Asian population. American Journal of Kidney Diseases, 2011. 58(1): p. 56-63.
2. Levey, A.S., et al., Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. Annals of internal medicine, 2006. 145(4): p. 247-254.
3. Botev, R., et al., The clinician and estimation of glomerular filtration rate by creatinine-based formulas: current limitations and quo vadis. Clinical Journal of the American Society of Nephrology, 2011. 6(4): p. 937-950.
4. Delanaye, P., H. Pottel, and R. Botev, Con: Should we abandon the use of the MDRD equation in favour of the CKD-EPI equation? Nephrology Dialysis Transplantation, 2013. 28(6): p. 1396-1403.
5. Schaeffner, E.S., et al., Two novel equations to estimate kidney function in persons aged 70 years or older. Annals of internal medicine, 2012. 157(7): p. 471-481.
6. Rehberg, P.B., Studies on kidney function: the rate of filtration and reabsorption in the human kidney. Biochemical Journal, 1926. 20(3): p. 447.
7. Heymsfield, S.B., et al., Measurement of muscle mass in humans: validity of the 24-hour urinary creatinine method. The American journal of clinical nutrition, 1983. 37(3): p. 478-494.
8. Mayersohn, M., K.A. Conrad, and R. Achari, The influence of a cooked meat meal on creatinine plasma concentration and creatinine clearance. British journal of clinical pharmacology, 1983. 15(2): p. 227-230.
9. Clausen, J., Proteins in normal cerebrospinal fluid not found in serum. Proceedings of the Society for Experimental Biology and Medicine, 1961. 107(1): p. 170-172.
10. Abrahamson, M., et al., Structure and expression of the human cystatin C gene. Biochemical journal, 1990. 268(2): p. 287-294.
11. Tenstad, O., et al., Renal handling of radiolabelled human cystatin C in the rat. Scandinavian journal of clinical and laboratory investigation, 1996. 56(5): p. 409-414.
12. Grubb, A., et al., Serum concentration of cystatin C, factor D and β2‐microglobulin as a measure of glomerular filtration rate. Acta Medica Scandinavica, 1985. 218(5): p. 499-503.
13. Stevens, L.A., et al., Factors other than glomerular filtration rate affect serum cystatin C levels. Kidney international, 2009. 75(6): p. 652-660.
14. Galteau, M.-M., et al., Determination of serum cystatin C: biological variation and reference values. 2001.
15. Fricker, M., et al., Impact of thyroid dysfunction on serum cystatin C. Kidney international, 2003. 63(5): p. 1944-1947.
16. Gagneux-Brunon, A., C. Mariat, and P. Delanaye, Cystatin C in HIV-infected patients: promising but not yet ready for prime time. Nephrology Dialysis Transplantation, 2012. 27(4): p. 1305-1313.
17. Segarra, A., et al., Assessing glomerular filtration rate in hospitalized patients: a comparison between CKD-EPI and four cystatin C-based equations. Clinical Journal of the American Society of Nephrology: CJASN, 2011. 6(10): p. 2411.
18. Seronie-Vivien, S., et al., Cystatin C: current position and future prospects. Clinical chemistry and laboratory medicine, 2008. 46(12): p. 1664-1686.
19. EFFERSØE, P., Relationship between endogenous 24‐hour creatinine clearance and serum creatinine concentration in patients with chronic renal disease. Acta Medica Scandinavica, 1957. 156(6): p. 429-434.
20. Cockcroft, D.W. and H. Gault, Prediction of creatinine clearance from serum creatinine. Nephron, 1976. 16(1): p. 31-41.
21. Levey, A.S., et al., A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Annals of internal medicine, 1999. 130(6): p. 461-470.
22. Delanaye, P. and J.-M. Krzesinski, Indexing of renal function parameters by body surface area: intelligence or folly? Nephron Clinical practice, 2011. 119(4): p. c289-c292.
23. Millar, J.A., The Cockroft and Gault formula for estimation of creatinine clearance: a friendly deconstruction. The New Zealand Medical Journal (Online), 2012. 125(1350).
24. Eriksen, B.O., et al., GFR normalized to total body water allows comparisons across genders and body sizes. Journal of the American Society of Nephrology: JASN, 2011. 22(8): p. 1517.
25. Nyman, H.A., et al., Comparative evaluation of the Cockcroft‐Gault Equation and the Modification of Diet in Renal Disease (MDRD) study equation for drug dosing: an opinion of the Nephrology Practice and Research Network of the American College of Clinical Pharmacy. Pharmacotherapy: The Journal of Human Pharmacology and Drug Therapy, 2011. 31(11): p. 1130-1144.
26. Macisaac, R.J., et al., Estimating glomerular filtration rate in diabetes: a comparison of cystatin-C-and creatinine-based methods. Diabetologia, 2006. 49: p. 1686-1689.
27. Rule, A.D., et al., Using serum creatinine to estimate glomerular filtration rate: accuracy in good health and in chronic kidney disease. Annals of internal medicine, 2004. 141(12): p. 929-937.
28. Murthy, K., et al., Variation in the serum creatinine assay calibration: a practical application to glomerular filtration rate estimation. Kidney international, 2005. 68(4): p. 1884-1887.
29. Schwartz, G.J., et al., Improved equations estimating GFR in children with chronic kidney disease using an immunonephelometric determination of cystatin C. Kidney international, 2012. 82(4): p. 445-453.
30. Levey, A.S., et al., A new equation to estimate glomerular filtration rate. Annals of internal medicine, 2009. 150(9): p. 604-612.
31. Delanaye, P., et al., MDRD or CKD-EPI study equations for estimating prevalence of stage 3 CKD in epidemiological studies: which difference? Is this difference relevant? BMC nephrology, 2010. 11: p. 1-7.
32. Matsushita, K., et al., Risk implications of the new CKD Epidemiology Collaboration (CKD-EPI) equation compared with the MDRD Study equation for estimated GFR: the Atherosclerosis Risk in Communities (ARIC) Study. American journal of kidney diseases, 2010. 55(4): p. 648-659.
33. White, S.L., et al., Comparison of the prevalence and mortality risk of CKD in Australia using the CKD Epidemiology Collaboration (CKD-EPI) and Modification of Diet in Renal Disease (MDRD) Study GFR estimating equations: the AusDiab (Australian Diabetes, Obesity and Lifestyle) Study. American journal of kidney diseases, 2010. 55(4): p. 660-670.
34. Murata, K., et al., Relative performance of the MDRD and CKD-EPI equations for estimating glomerular filtration rate among patients with varied clinical presentations. Clinical journal of the American Society of Nephrology: CJASN, 2011. 6(8): p. 1963.
35. Björk, J., et al., Validation of the Lund–Malmö, Chronic Kidney Disease Epidemiology (CKD-EPI) and Modification of Diet in Renal Disease (MDRD) equations to estimate glomerular filtration rate in a large Swedish clinical population. Scandinavian journal of urology and nephrology, 2012. 46(3): p. 212-222.
36. Buron, F., et al., Estimating glomerular filtration rate in kidney transplant recipients: performance over time of four creatinine-based formulas. Transplantation, 2011. 92(9): p. 1005-1011.
37. Bargnoux, A., et al., Accuracy of GFR predictive equations in renal transplantation: Validation of a new turbidimetric cystatin C assay on Architect c8000®. Clinical biochemistry, 2012. 45(1-2): p. 151-153.
38. White, C.A., et al., Estimating glomerular filtration rate in kidney transplantation: is the new chronic kidney disease epidemiology collaboration equation any better? Clinical chemistry, 2010. 56(3): p. 474-477.
39. Stevens, L.A., et al., Comparative performance of the CKD Epidemiology Collaboration (CKD-EPI) and the Modification of Diet in Renal Disease (MDRD) Study equations for estimating GFR levels above 60 mL/min/1.73 m2. American Journal of Kidney Diseases, 2010. 56(3): p. 486-495.
40. Harman, G., et al., Accuracy of cystatin C-based estimates of glomerular filtration rate in kidney transplant recipients: a systematic review. Nephrology Dialysis Transplantation, 2013. 28(3): p. 741-757.
41. Masson, I., et al., GFR estimation using standardized cystatin C in kidney transplant recipients. American journal of kidney diseases, 2013. 61(2): p. 279-284.
42. Delanaye, P., et al., Normal reference values for glomerular filtration rate: what do we really know? Nephrology Dialysis Transplantation, 2012. 27(7): p. 2664-2672.
43. Van Den Noortgate, N.J., et al., Serum cystatin C concentration compared with other markers of glomerular filtration rate in the old old. Journal of the American Geriatrics Society, 2002. 50(7): p. 1278-1282.
44. Flamant, M., et al., GFR estimation using the Cockcroft-Gault, MDRD study, and CKD-EPI equations in the elderly. American journal of kidney diseases, 2012. 60(5): p. 847-849.
45. Kilbride, H.S., et al., Accuracy of the MDRD (Modification of Diet in Renal Disease) study and CKD-EPI (CKD Epidemiology Collaboration) equations for estimation of GFR in the elderly. American Journal of Kidney Diseases, 2013. 61(1): p. 57-66.
46. Parveen, S., et al., Prevalence of MRSA colonization among healthcare-workers and effectiveness of decolonization regimen in ICU of a Tertiary care Hospital, Lahore, Pakistan. Advancements in Life Sciences, 2020. 8(1): p. 38-41.
47. Sohail, M., et al., Molecular Characterization of Community-and Hospital-Acquired Methicillin-Resistant Staphylococcus aureus Isolates during COVID-19 Pandemic. Antibiotics, 2023. 12(1): p. 157.
48. Ahmed, N., et al., Antibiotic resistance profile in relation to virulence genes fimH, hlyA and usp of uropathogenic E. coli isolates in Lahore, Pakistan. Trop. Biomed, 2019. 36: p. 559-568.
49. Poggio, E.D., et al., Performance of the Cockcroft-Gault and modification of diet in renal disease equations in estimating GFR in ill hospitalized patients. American journal of kidney diseases, 2005. 46(2): p. 242-252.
50. Delanaye, P., et al., Cystatin C or creatinine for detection of stage 3 chronic kidney disease in anorexia nervosa. Nephron Clinical Practice, 2008. 110(3): p. c158-c163.
51. Xirouchakis, E., et al., Comparison of cystatin C and creatinine-based glomerular filtration rate formulas with 51Cr-EDTA clearance in patients with cirrhosis. Clinical journal of the American Society of Nephrology: CJASN, 2011. 6(1): p. 84.
52. Grootendorst, D.C., et al., The MDRD formula does not reflect GFR in ESRD patients. Nephrology dialysis transplantation, 2011. 26(6): p. 1932-1937.
53. Carrie, B.J., et al., Creatinine: an inadequate filtration marker in glomerular diseases. The American journal of medicine, 1980. 69(2): p. 177-182.
54. Branten, A.J., G. Vervoort, and J.F. Wetzels, Serum creatinine is a poor marker of GFR in nephrotic syndrome. Nephrology Dialysis Transplantation, 2005. 20(4): p. 707-711.
55. Delanghe, J.R., How to estimate GFR in children. Nephrology Dialysis Transplantation, 2009. 24(3): p. 714-716.
56. Finney, H., et al., Reference ranges for plasma cystatin C and creatinine measurements in premature infants, neonates, and older children. Archives of disease in childhood, 2000. 82(1): p. 71-75.
57. Schwartz, G.J., et al., New equations to estimate GFR in children with CKD. Journal of the American Society of Nephrology: JASN, 2009. 20(3): p. 629.
58. Ebert, N., et al., Assessment of kidney function: clinical indications for measured GFR. Clinical kidney journal, 2021. 14(8): p. 1861-1870.
59. Goldwasser, P., A. Aboul-Magd, and M. Maru, Race and creatinine excretion in chronic renal insufficiency. American journal of kidney diseases, 1997. 30(1): p. 16-22.
60. Lewis, J., et al., Comparison of cross-sectional renal function measurements in African Americans with hypertensive nephrosclerosis and of primary formulas to estimate glomerular filtration rate. American journal of kidney diseases, 2001. 38(4): p. 744-753.
61. Delanaye, P., et al., Are the creatinine-based equations accurate to estimate glomerular filtration rate in African American populations? Clinical Journal of the American Society of Nephrology, 2011. 6(4): p. 906-912.
62. van Deventer, H.E., et al., A comparison of cystatin C-and creatinine-based prediction equations for the estimation of glomerular filtration rate in black South Africans. Nephrology Dialysis Transplantation, 2011. 26(5): p. 1553-1558.
63. Maple-Brown, L.J., et al., Accurate assessment of kidney function in indigenous Australians: the estimated GFR study. American Journal of Kidney Diseases, 2012. 60(4): p. 680-682.
64. Delanaye, P., et al., Estimating glomerular filtration rate in Asian subjects: where do we stand? Kidney international, 2011. 80(5): p. 439-440.
65. Teo, B.W., et al., GFR estimating equations in a multiethnic Asian population. American Journal of Kidney Diseases, 2011. 58(1): p. 56-63.
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Aug 7, 2023
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Amer Hayat Khan, Irfanullah Khan, Jamshaid Ahmad, Ijaz Ahmad, Anam Farzand, Siti Maisharah Sheikh Ghadzi, Kamarul Imran Musa, Azreen Syazril Adnan, & Md Asiful Islam. (2023). CLINICAL PRACTICE BASE EGFR EQUATIONS AND THEIR APPLICATIONS IN DIFFERENT CKD POPULATIONS: A NARRATIVE REVIEW. Journal of Population Therapeutics and Clinical Pharmacology, 30(16), 491–501. https://doi.org/10.53555/jptcp.v30i16.2479
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Author Biographies
Amer Hayat Khan
Discipline of Clinical Pharmacy, School of Pharmaceutical Sciences, Universiti Sains Malaysia, 11800, Gelugor, Penang, Malaysia
Irfanullah Khan
Chronic Kidney Disease Resource Centre, School of Medical Sciences, Health Campus, Universiti Sains Malaysia, Kubang Kerian 16150, Kelantan, Malaysia
Jamshaid Ahmad
Department of Medical Education, Sharif Medical and Dental College, Lahore 54000, Punjab, Pakistan
Ijaz Ahmad
Department of Allied Health Science, Superior University, Lahore 54000, Pakistan
Anam Farzand
Department of Allied Health Science, Superior University, Lahore 54000, Pakistan
Siti Maisharah Sheikh Ghadzi
Discipline of Clinical Pharmacy, School of Pharmaceutical Sciences, Universiti Sains Malaysia, Penang 11800, Malaysia
Kamarul Imran Musa
Department of Community Medicine, School of Medical Sciences, Health Campus, Universiti Sains Malaysia, Kubang Kerian 16150, Malaysia
Azreen Syazril Adnan
Consultant Nephrologist and Physician, Advanced Medical & Dental Institute, Universiti Sains Malaysia, Bertam, Jalan Tun Hamdan Sheikh Tahir, Kepala Batas 13200, Penang, Malaysia
Md Asiful Islam
WHO Collaborating Centre for Global Women’s Health, Institute of Metabolism and Systems Research, University of Birmingham, Birmingham B15 2TT, UK