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Dialyse aktuell 2015; 19(6): 299-303
DOI: 10.1055/s-0035-1562918
Nephrologie
© Georg Thieme Verlag Stuttgart · New York

Bestimmung der Nierenfunktion im Alter – Was ist zu beachten?

Determination of renal function in the eldery – What needs to be considered?
Daniel Kitterer
,
Elke S Schaeffner
,
Joerg Latus
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Publication History

Publication Date:
10 August 2015 (online)

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Zusammenfassung

Eine eingeschränkte Nierenfunktion hat eine hohe Prävalenz im Kollektiv der Älteren und ist zudem ein unabhängiger Risikofaktor für kardiovaskuläre Ereignisse. Die Leitlinien der KDIGO-Organisation (KDIGO: Kidney Disease: Improving Global Outcomes) definiert eine errechnete oder gemessene glomeruläre Filtrationsrate (GFR) von weniger als 60 ml/min/1,73 m2 als eine eingeschränkte Nierenfunktion (altersunabhängig). Goldstandardverfahren zur Bestimmung der Nierenfunktion sind z.B. die Inulin- oder Iohexolclearance. In der klinischen Praxis wird die Nierenfunktion jedoch nicht direkt gemessen, sondern vielmehr über endogene Biomarker und mittels mathematischer Formeln abgeschätzt. Beruhend auf Untersuchungen an einer gesunden, hauptsächlich kaukasischen US-amerikanischen Kohorte wurde eine jährliche, altersabhängige Abnahme der glomerulären Filtrationsrate (GFR) von ca. 0,75 ml/min/1,73 m2 beobachtet. Die aktuellen KDIGO-Guidelines teilen die Stadien der chronischen Niereninsuffizienz beruhend auf der „estimated glomerular filtration rate“ (eGFR) und dem Ausmaß der Albuminurie ein. Eine exakte Einteilung der Stadien hat insbesondere im Hinblick auf die Dosisanpassung einer Pharmakotherapie eine praktische klinische Relevanz. Weiterhin hat die Stadieneinteilung auch eine prognostische Relevanz. Die Bestimmung der Nierenfunktion ist bei älteren und vor allem bei hoch betagten Menschen (> 80 Jahren) nicht trivial – einerseits aufgrund einer möglichen „physiologischen“ Abnahme der Nierenfunktion im Alter und andererseits aufgrund nicht gut evaluierter Messparameter. Sowohl die MDRD- (Modification of Diet in Renal Diseases) als auch die CKD-EPI-Formel (CKD-EPI: Chronic Kidney Disease Epidemiology Collaboration) benutzen standardmäßig das Serumkreatinin als Biomarker. Beide Formeln sind jedoch im Kollektiv der älteren Patienten entweder gar nicht (MDRD) oder nur an einer kleinen Personenzahl validiert. Die Bestimmung des Cystatin C (muskelmasseunabhängiger Biomarker) zur Abschätzung der Nierenfunktion scheint beim älteren Menschen Vorteile zu haben. Seit dem Jahr 2012 stehen uns durch die Ergebnisse der Berliner Initiative Studie (BIS) erstmals Daten zur Abschätzung der Nierenfunktion beim hochbetagten Menschen zur Verfügung.

Summary

Impaired renal function is associated with an increased risk of adverse outcomes, including cardiovascular events, development of end-stage renal disease and death. Furthermore, the prevalence of chronic kidney disease (CKD) increases with advancing age. The Kidney Disease: Improving Global Outcomes (KDIGO) Guidelines define a glomerular filtration rate (GFR) less than 60 ml/min/1.73 m2 as chronic kidney disease (independently from age). Gold standards for the determination of renal function are e.g. inulin or iohexol clearance, but this is impractical for large-scale application. In everyday clinical practice, mostly creatinine-based equations to estimate GFR (eGFR) were used. Estimation of GFR is essential for the evaluation of patients with CKD, to classify into stages according to the level of GFR and to prevent further complications, e.g. correct dosage of drugs cleared by the kidney so as to avoid potential drug toxicity. When focusing on elderly population, it must be taken into account that there is a physiological decrease of GFR from 0.75–1.0 ml/min/year. Therefore, determination of kidney function in very elderly people (> 80 years) is not trivial because of the physiological decrease of GFR and, on the other hand, current equations to estimate glomerular filtration rate (GFR) are not validated and may misclassify elderly persons in terms of their stage of chronic kidney disease. Both used formulas, Modification of Diet in Renal Diseases (MDRD) and Chronic Kidney Disease Epidemiology Collaboration, (CKD-EPI) are based on serum creatinine or cystatin C and were not validated in elderly patients. Measurements of cystatin C to estimate the GFR in elderly or very elderly people might be superior. Since 2012, for the first time we have data from the Berlin Initiative Study (BIS) to estimate GFR in elderly and very elderly people.

Key words

cystatin C - BIS - CKD-EPI - MDRD - chronic kidney disease
 

  • Literatur

  • 1 Statistisches Bundesamt, Gruppe ID, Pressestelle, Gruppe VIA, „Demografische Modellrechnungen“. Bevölkerung Deutschlands bis 2060. 12. koordinierte Bevölkerungsvorausberechnung. Begleitmaterial zur Pressekonferenz am 18. November 2009 in Berlin.
    Google Scholar
  • 2 Coresh J, Astor BC, Greene T et al. Prevalence of chronic kidney disease and decreased kidney function in the adult us population: Third national health and nutrition examination survey. Am J Kidney Dis 2003; 41: 1-12
    CrossrefGoogle Scholar
  • 3 Anavekar NS, Pfeffer MA. Cardiovascular risk in chronic kidney disease. Kidney Int Suppl 2004; 92: S11-S15
    Google Scholar
  • 4 Anavekar NS, McMurray JJ, Velazquez EJ et al. Relation between renal dysfunction and cardiovascular outcomes after myocardial infarction. N Engl J Med 2004; 351: 1285-1295
    CrossrefGoogle Scholar
  • 5 Fried LF, Lee JS, Shlipak M et al. Chronic kidney disease and functional limitation in older people: Health, aging and body composition study. J Am Geriatr Soc 2006; 54: 750-756
    CrossrefGoogle Scholar
  • 6 Lindeman RD, Tobin J, Shock NW. Longitudinal studies on the rate of decline in renal function with age. J Am Geriatr Soc 1985; 33: 278-285
    CrossrefGoogle Scholar
  • 7 Davies DF, Shock NW. Age changes in glomerular filtration rate, effective renal plasma flow, and tubular excretory capacity in adult males. J Clin Invest 1950; 29: 496-507
    CrossrefGoogle Scholar
  • 8 Florijn KW, Barendregt JN, Lentjes EG et al. Glomerular filtration rate measurement by “single-shot” injection of inulin. Kidney Int 1994; 46: 252-259
    CrossrefGoogle Scholar
  • 9 Brandstrom E, Grzegorczyk A, Jacobsson L et al. GFR measurement with iohexol and 51cr-EDTA. A comparison of the two favoured GFR markers in Europe. Nephrol Dial Transplant 1998; 13: 1176-1182
    CrossrefGoogle Scholar
  • 10 Aloia JF, Vaswani A, Feuerman M et al. Differences in skeletal and muscle mass with aging in black and white women. Am J Physiol Endocrinol Metab 2000; 278: E1153-E1157
    Google Scholar
  • 11 Matsushita K, Selvin E, Bash LD 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. Am J Kidney Dis 2010; 55: 648-659
    CrossrefGoogle Scholar
  • 12 White SL, Polkinghorne KR, Atkins RC, Chadban SJ. 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. Am J Kidney Dis 2010; 55: 660-670
    CrossrefGoogle Scholar
  • 13 Alagiakrishnan K, Senthilselvan A. Low agreement between the modified diet and renal disease formula and the Cockcroft-Gault formula for assessing chronic kidney disease in cognitively impaired elderly outpatients. Postgrad Med 2010; 122: 41-45
    CrossrefGoogle Scholar
  • 14 Michels WM, Grootendorst DC, Verduijn M et al. Performance of the Cockcroft-Gault, MDRD, and new CKD-EPI formulas in relation to GFR, age, and body size. Clin J Am Soc Nephrol 2010; 5: 1003-1009
    CrossrefGoogle Scholar
  • 15 Verbeeck RK, Musuamba FT. Pharmacokinetics and dosage adjustment in patients with renal dysfunction. Eur J Clin Pharmacol 2009; 65: 757-773
    CrossrefGoogle Scholar
  • 16 Blix HS, Viktil KK, Moger TA, Reikvam A. Use of renal risk drugs in hospitalized patients with impaired renal function--an underestimated problem?. Nephrol Dial Transplant 2006; 21: 3164-3171
    CrossrefGoogle Scholar
  • 17 Corsonello A, Pedone C, Lattanzio F et al.; Gruppo Italiano di Farmacovigilanza nell'Anziano (GIFA). Association between glomerular filtration rate and adverse drug reactions in elderly hospitalized patients: The role of the estimating equation. Drugs Aging 2011; 28: 379-390
    CrossrefGoogle Scholar
  • 18 Hug BL, Witkowski DJ, Sox CM et al. Occurrence of adverse, often preventable, events in community hospitals involving nephrotoxic drugs or those excreted by the kidney. Kidney Int 2009; 76: 1192-1198
    CrossrefGoogle Scholar
  • 19 Levey AS, de Jong PE, Coresh J et al. The definition, classification, and prognosis of chronic kidney disease: a KDIGO controversies conference report. Kidney Int 2011; 80: 17-28
    CrossrefGoogle Scholar
  • 20 Murata K, Baumann NA, Saenger AK et al. Relative performance of the MDRD and CKD-EPI equations for estimating glomerular filtration rate among patients with varied clinical presentations. Clin J Am Soc Nephrol 2011; 6: 1963-1972
    CrossrefGoogle Scholar
  • 21 Poggio ED, Rule AD, Tanchanco R et al. Demographic and clinical characteristics associated with glomerular filtration rates in living kidney donors. Kidney Int 2009; 75: 1079-1087
    CrossrefGoogle Scholar
  • 22 Stevens LA, Schmid CH, Greene T 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. Am J Kidney Dis 2010; 56: 486-495
    CrossrefGoogle Scholar
  • 23 Roberts GW, Ibsen PM, Schioler CT. Modified diet in renal disease method overestimates renal function in selected elderly patients. Age Ageing 2009; 38: 698-703
    CrossrefGoogle Scholar
  • 24 Schaeffner ES, Ebert N, Delanaye P et al. Two novel equations to estimate kidney function in persons aged 70 years or older. Ann Intern Med 2012; 157: 471-481
    CrossrefGoogle Scholar
  • 25 Hellden A, Odar-Cederlof I, Nilsson G et al. Renal function estimations and dose recommendations for dabigatran, gabapentin and valaciclovir: A data simulation study focused on the elderly. BMJ Open 2013; 3 pii: e002686
    Google Scholar
  • 26 Lopes MB, Araujo LQ, Passos MT et al. Estimation of glomerular filtration rate from serum creatinine and cystatin c in octogenarians and nonagenarians. BMC Nephrol 2013; 14: 265-265
    CrossrefGoogle Scholar
  • 27 Shlipak MG, Katz R, Kestenbaum B et al. Rate of kidney function decline in older adults: A comparison using creatinine and cystatin c. Am J Nephrol 2009; 30: 171-178
    CrossrefGoogle Scholar
  • 28 Fliser D, Ritz E. Serum cystatin c concentration as a marker of renal dysfunction in the elderly. Am J Kidney Dis 2001; 37: 79-83
    CrossrefGoogle Scholar
  • 29 Horio M, Imai E, Yasuda Y et al. Performance of serum cystatin c versus serum creatinine as a marker of glomerular filtration rate as measured by inulin renal clearance. Clin Exp Nephrol 2011; 15: 868-876
    CrossrefGoogle Scholar
  • 30 Fraser SD, Aitken G, Taal MW et al. Exploration of chronic kidney disease prevalence estimates using new measures of kidney function in the health survey for England. PLoS One 2015; 10 e0118676
    Google Scholar
  • 31 Okura T, Jotoku M, Irita J et al. Association between cystatin c and inflammation in patients with essential hypertension. Clin Exp Nephrol 2010; 14: 584-588
    CrossrefGoogle Scholar
  • 32 Kimmel M, Braun N, Alscher MD. Influence of thyroid function on different kidney function tests. Kidney Blood Press Res 2012; 35: 9-17
    CrossrefGoogle Scholar
  • 33 Pawelec G, Goldeck D, Derhovanessian E. Inflammation, ageing and chronic disease. Curr Opin Immunol 2014; 29: 23-28
    CrossrefGoogle Scholar
  • 34 Berhane AM, Weil EJ, Knowler WC et al. Albuminuria and estimated glomerular filtration rate as predictors of diabetic end-stage renal disease and death. Clin J Am Soc Nephrol 2011; 6: 2444-2451
    CrossrefGoogle Scholar
  • 35 van der Velde M, Halbesma N, de Charro FT et al. Screening for albuminuria identifies individuals at increased renal risk. J Am Soc Nephrol 2009; 20: 852-862
    CrossrefGoogle Scholar
  • 36 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: S1-S150
    CrossrefGoogle Scholar
  • 37 Chronic Kidney Disease Prognosis Consortium. Matsushita K, van der Velde M, Astor BC et al. Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: a collaborative meta-analysis. Lancet 2010; 375: 2073-2081
    CrossrefGoogle Scholar
  • 38 Garg AX, Kiberd BA, Clark WF et al. Albuminuria and renal insufficiency prevalence guides population screening: Results from the NHANES III. Kidney Int 2002; 61: 2165-2175
    CrossrefGoogle Scholar
  • 39 Glassock RJ, Winearls C. An epidemic of chronic kidney disease: Fact or fiction?. Nephrol Dial Transplant 2008; 23: 1117-1121
    CrossrefGoogle Scholar
  • 40 Peralta CA, Shlipak MG, Judd S et al. Detection of chronic kidney disease with creatinine, cystatin C, and urine albumin-to-creatinine ratio and association with progression to end-stage renal disease and mortality. JAMA 2011; 305: 1545-1552
    CrossrefGoogle Scholar
  • 41 Levey AS, Coresh J, Greene T et al.; Chronic Kidney Disease Epidemiology Collaboration. Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. Ann Intern Med 2006; 145: 247-254
    CrossrefGoogle Scholar
  • 42 Levey AS, Stevens LA, Schmid CH et al.; CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration). A new equation to estimate glomerular filtration rate. Ann Intern Med 2009; 150: 604-612
    CrossrefPubMedGoogle Scholar
  • 43 Inker LA, Schmid CH, Tighiouart H et al.; CKD-EPI Investigators. Estimating glomerular filtration rate from serum creatinine and cystatin C. N Engl J Med 2012; 367: 20-29
    CrossrefGoogle Scholar