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Klinische Implikationen der geschätzten glomerulären Filtrationsrate

Clinical implications of the estimated glomerular filtration rate

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Zusammenfassung

Eine korrekte Bestimmung der glomerulären Filtrationsrate (GFR) ist gleichermaßen notwendig und schwierig. Goldstandardmethoden wie die Messung der Inulin-Clearance sind für den klinischen Gebrauch nicht praktikabel, sodass die Nierenfunktion mithilfe leichter messbarer endogener Biomarker abgeschätzt werden muss. Die Plasmakonzentrationen der Filtrationsmarker Kreatinin und Cystatin C lassen allein keine einfache Aussage über die Nierenfunktion zu, da ihre Konzentrationen nicht linear mit und auch nicht ausschließlich von der GFR abhängen. Daher versuchen Formeln, die GFR mathematisch anhand einfach verfügbarer Parameter abzuschätzen. Aktuell am gebräuchlichsten ist die Formel MDRD (nach der Modification of Diet in Renal Disease Study) oder CKD-EPI (nach der Chronic Kidney Disease Epidemiology Collaboration). Für ältere Menschen stehen u. a. die Formeln BIS‑1 und BIS‑2 (nach der Berlin Initiative Study) zur Verfügung. Inwieweit die geschätzte („estimated“) Filtrationsrate (eGFR) der wahren GFR nahekommt, hängt von verschiedenen Faktoren ab. Die Genauigkeit der Formeln ist geringer bei GFR-Werten über 60 ml/min · 1,73 m2KOF, akuten Schwankungen der GFR und bei extremen individuellen Körpermerkmalen, insbesondere bei sehr hoher oder sehr geringer Muskelmasse. Eine eGFR um oder knapp unter 60 ml/min · 1,73 m2KOF allein kann bei älteren Individuen nicht sicher zwischen alters- und krankheitsbedingtem GFR-Verlust diskriminieren. Renal eliminierte Medikamente sollten dennoch anhand der eGFR dosiert werden.

Abstract

A correct determination of the glomerular filtration rate (GFR) is necessary and at the same time difficult. Using gold standard methods, such as measurement of inulin clearance, are not feasible in clinical practice raising the need for methods to estimate GFR using easy to measure endogenous biomarkers. Plasma concentrations of the filtration markers creatinine and cystatin C alone are not adequate to easily calculate kidney function. This is mainly due to a non-linear relationship between plasma concentrations and GFR and GFR-independent factors influencing the plasma concentrations. Therefore, formulae have been developed to estimate GFR using easily available variables. Currently, the most useful formulae are those developed by the modification of diet in renal disease (MDRD) study and more recently by the chronic kidney disease epidemiology (CKD-EPI) collaboration. For older individuals some specifically validated formulae were developed some years ago, among them the Berlin initiative study 1 (BIS-1) and BIS‑2 formulae. The accuracy of the estimated filtration rate (eGFR) with respect to the true GFR depends on various factors. The accuracy of the formula is especially low in the GFR range above 60 ml/min · 1.73 m2, during recent or rapid changes of GFR and in the case of extreme physical traits, especially a very high or low muscle mass. In older individuals an eGFR around 60 ml/min · 1.73 m2 alone is not sufficient to discriminate between age-related and disease-related decline in GFR. Nonetheless dosing of medications with predominantly renal excretion should be made according to the eGFR.

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Literatur

  1. Anonymous (2013) Chapter 1: Definition and classification of CKD. Kidney Int Suppl 3:19–62

    Article  Google Scholar 

  2. Anonymous (2002) K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Am J Kidney Dis 39:S1–S266

    Google Scholar 

  3. Bokenkamp A, Ciarimboli G, Dieterich C (2001) Cystatin C in a rat model of end-stage renal failure. Ren Fail 23:431–438

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  5. Delanaye P, Ebert N, Melsom T et al (2016) Iohexol plasma clearance for measuring glomerular filtration rate in clinical practice and research: a review. Part 1: How to measure glomerular filtration rate with iohexol? Clin Kidney J 9:682–699

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Gaspari F, Perico N, Matalone M et al (1998) Precision of plasma clearance of iohexol for estimation of GFR in patients with renal disease. J Am Soc Nephrol 9:310–313

    Article  CAS  PubMed  Google Scholar 

  7. Groesbeck D, Köttgen A, Parekh R et al (2008) Age, gender, and race effects on cystatin C levels in US adolescents. Clin J Am Soc Nephrol 3:1777–1785

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Hallan SI, Matsushita K, Sang Y et al (2012) Age and association of kidney measures with mortality and end-stage renal disease. JAMA 308:2349–2360

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Husain SA, Willey JZ, Park MY et al (2018) Creatinine- versus cystatin C‑based renal function assessment in the Northern Manhattan Study. PLoS ONE 13:e206839

    Article  PubMed  PubMed Central  Google Scholar 

  10. Knight EL, Verhave JC, Spiegelman D et al (2004) Factors influencing serum cystatin C levels other than renal function and the impact on renal function measurement. Kidney Int 65:1416–1421

    Article  CAS  PubMed  Google Scholar 

  11. Levey AS, Coresh J, Greene T et al (2006) Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. Ann Intern Med 145:247–254

    Article  CAS  PubMed  Google Scholar 

  12. Levey AS, Stevens LA, Schmid CH et al (2009) A new equation to estimate glomerular filtration rate. Ann Intern Med 150:604–612

    Article  PubMed  PubMed Central  Google Scholar 

  13. Levey AS, Titan SM, Powe NR et al (2020) Kidney disease, race, and GFR estimation. Clin J Am Soc Nephrol 15:1203–1212

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Lindeman RD, Tobin J, Shock NW (1985) Longitudinal studies on the rate of decline in renal function with age. J Am Geriatr Soc 33:278–285

    Article  CAS  PubMed  Google Scholar 

  15. Macdonald J, Marcora S, Jibani M et al (2006) GFR estimation using cystatin C is not independent of body composition. Am J Kidney Dis 48:712–719

    Article  CAS  PubMed  Google Scholar 

  16. Manetti L, Pardini E, Genovesi M et al (2005) Thyroid function differently affects serum cystatin C and creatinine concentrations. J Endocrinol Invest 28:346–349

    Article  CAS  PubMed  Google Scholar 

  17. Matzke GR, Aronoff GR, Atkinson AJ Jr. et al (2011) Drug dosing consideration in patients with acute and chronic kidney disease—a clinical update from Kidney Disease: Improving Global Outcomes (KDIGO). Kidney Int 80:1122–1137

    Article  CAS  PubMed  Google Scholar 

  18. Newman DJ (2002) Cystatin C. Ann Clin Biochem 39:89–104

    Article  CAS  PubMed  Google Scholar 

  19. Rowe C, Sitch AJ, Barratt J et al (2019) Biological variation of measured and estimated glomerular filtration rate in patients with chronic kidney disease. Kidney Int 96:429–435

    Article  PubMed  Google Scholar 

  20. Rule AD, Bergstralh EJ, Slezak JM et al (2006) Glomerular filtration rate estimated by cystatin C among different clinical presentations. Kidney Int 69:399–405

    Article  CAS  PubMed  Google Scholar 

  21. Rule AD, Larson TS, Bergstralh EJ et al (2004) Using serum creatinine to estimate glomerular filtration rate: accuracy in good health and in chronic kidney disease. Ann Intern Med 141:929–937

    Article  CAS  PubMed  Google Scholar 

  22. Schaeffner ES, Ebert N, Delanaye P et al (2012) Two novel equations to estimate kidney function in persons aged 70 years or older. Ann Intern Med 157:471–481

    Article  PubMed  Google Scholar 

  23. Shemesh O, Golbetz H, Kriss JP et al (1985) Limitations of creatinine as a filtration marker in glomerulopathic patients. Kidney Int 28:830–838

    Article  CAS  PubMed  Google Scholar 

  24. Sjostrom P, Tidman M, Jones I (2005) Determination of the production rate and non-renal clearance of cystatin C and estimation of the glomerular filtration rate from the serum concentration of cystatin C in humans. Scand J Clin Lab Invest 65:111–124

    Article  CAS  PubMed  Google Scholar 

  25. Smith HW (1951) The kidney: structure and function in health and disease. Oxford University Press, New York

    Google Scholar 

  26. Stevens LA, Levey AS (2009) Measured GFR as a confirmatory test for estimated GFR. J Am Soc Nephrol 20:2305–2313

    Article  PubMed  Google Scholar 

  27. Tenstad O, Roald AB, Grubb A et al (1996) Renal handling of radiolabelled human cystatin C in the rat. Scand J Clin Lab Invest 56:409–414

    Article  CAS  PubMed  Google Scholar 

  28. Wesson LG (1969) Physiology of the human kidney. Grune & Stratton, New York

    Google Scholar 

  29. Wyss M, Kaddurah-Daouk R (2000) Creatine and creatinine metabolism. Physiol Rev 80:1107–1213

    Article  CAS  PubMed  Google Scholar 

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Correspondence to Christian Weingart.

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C. Weingart und G.H. Wirnsberger geben an, dass kein Interessenkonflikt besteht.

Für diesen Beitrag wurden von den Autoren keine Studien an Menschen oder Tieren durchgeführt. Für die aufgeführten Studien gelten die jeweils dort angegebenen ethischen Richtlinien.

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Weingart, C., Wirnsberger, G.H. Klinische Implikationen der geschätzten glomerulären Filtrationsrate. Z Gerontol Geriat 54, 205–210 (2021). https://doi.org/10.1007/s00391-021-01839-1

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  • DOI: https://doi.org/10.1007/s00391-021-01839-1

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