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Association between Glomerular Filtration Rate and Adverse Drug Reactions in Elderly Hospitalized Patients

The Role of the Estimating Equation

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Abstract

Background: Reduced renal function increases the risk of adverse drug reactions (ADRs) to hydrosoluble drugs (hADRs). However, the ability of different equations to calculate estimated glomerular filtration rate (eGFR) or estimated creatinine clearance (eCCr) and thereby predict the risk of developing hADRs has not previously been compared.

Objective: The aim of this study was to investigate which of three different equations for estimating renal function (Cockcroft-Gault [CG], Modification of Diet in Renal Disease [MDRD] and Chronic Kidney Disease Epidemiology Collaboration [CKD-EPI]) was the most effective at predicting incident hADRs.

Methods: This multicentre study had an observational design and included 81 acute-care general (internal) or geriatric medicine wards in academic hospitals throughout Italy. Our series consisted of 10 442 hospitalized patients with a mean ± SD age of 70.2 ± 14.9 years enrolled in the GIFA study. The main outcome measures were incident ADRs during hospital stay. Data on these were collected and classified as hADRs or ADRs to liposoluble drugs (lADRs). Patients were grouped according to their eGFR (mL/min/1.73m2) or eCCr (mL/min): ≥90, 60–89.9, 45–59.9, 30–44.9 or <30.

Results: The multivariable adjusted risk of hADRs progressively increased with decreasing eGFR as determined by estimates of mL/min/1.73 m2 calculated using CKD-EPI (60–89.9: hazard ratio [HR] = 1.07 [95% CI 0.70, 1.72]; 45–59.9: HR = 1.62 [95% CI 1.0,2.69]; 30–44.9: HR = 2.13 [95% CI 1.24, 3.64]; <30: HR = 2.30 [95% CI 1.28, 4.14]) and, to a lesser extent, MDRD (60–89.9: HR = 1.15 [95% CI 0.75, 1.76]; 45–59.9: HR = 1.73 [95% CI 1.09, 2.73]; 30–44.9: HR = 2.14 [95% CI 1.30, 3.53]; <30: HR = 1.99 [95% CI 1.11, 3.57]) equations. The risk of hADRs also increased with lower eCCr, but only at CG eCCr <45mL/min (30–44.9: HR = 1.61 [95% CI 0.96, 2.77]; <30: HR = 1.76 [95% CI 1.0, 3.18]). Neither eGFR nor eCCr were associated with lADRs.

Conclusions: CKD-EPI-based estimates of eGFR outperformed MDRD-based estimates of eGFR and CG-based estimates of eCCr as a predictor of hADRs.

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References

  1. Hemmelgarn BR, Manns BJ, Lloyd A, et al. Relation between kidney function, proteinuria, and adverse outcomes. JAMA 2010 Feb 3; 303(5): 423–9

    Article  PubMed  CAS  Google Scholar 

  2. Go AS, Chertow GM, Fan D, et al. Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. N Engl J Med 2004 Sep 23; 351(13): 1296–305

    Article  PubMed  CAS  Google Scholar 

  3. Anavekar NS, McMurray JJ, Velazquez EJ, et al. Relation between renal dysfunction and cardiovascular outcomes after myocardial infarction. N Engl J Med 2004 Sep 23; 351(13): 1285–95

    Article  PubMed  CAS  Google Scholar 

  4. Corsonello A, Pedone C, Corica F, et al. Concealed renal insufficiency and adverse drug reactions in elderly hospitalized patients. Arch Intern Med 2005 Apr 11; 165(7): 790–5

    Article  PubMed  Google Scholar 

  5. Hanratty CG, McGlinchey P, Johnston GD, et al. Differential pharmacokinetics of digoxin in elderly patients. Drugs Aging 2000; 17(5): 353–62

    Article  PubMed  CAS  Google Scholar 

  6. Morike K, Schwab M, Klotz U. Use of aminoglycosides in elderly patients: pharmacokinetic and clinical considerations. Drugs Aging 1997; 10(4): 259–77

    Article  PubMed  CAS  Google Scholar 

  7. Sproule BA, Hardy BG, Shulman KI. Differential pharmacokinetics of lithium in elderly patients. Drugs Aging 2000; 16(3): 165–77

    Article  PubMed  CAS  Google Scholar 

  8. Raveh D, Kopyt M, Hite Y, et al. Risk factors for nephrotoxicity in elderly patients receiving once-daily aminoglycosides. QJM 2002 May; 95(5): 291–7

    Article  PubMed  CAS  Google Scholar 

  9. Pedone C, Corsonello A, Incalzi RA. Estimating renal function in older people: a comparison of three formulas. Age Ageing 2006 Mar; 35(2): 121–6

    Article  PubMed  Google Scholar 

  10. Carosella L, Pahor M, Pedone C, et al. Pharmaco-surveillance in hospitalized patients in Italy. Study design of the ‘Gruppo Italiano di Farmacovigilanza nell’Anziano’ (GIFA). Pharmacol Res 1999 Sep; 40(3): 287–95

    Article  PubMed  CAS  Google Scholar 

  11. World Health Organization (WHO). International drug monitoring: the role of the hospital. Geneva: WHO, 1969. WHO Technical Report Series No.: 425

    Google Scholar 

  12. Naranjo CA, Busto U, Sellers EM, et al. A method for estimating the probability of adverse drug reactions. Clin Pharmacol Ther 1981 Aug; 30(2): 239–45

    Article  PubMed  CAS  Google Scholar 

  13. Hardman GJ, Limbird LE, Goodman Gilman A. Goodman and Gilman’s: the pharmacological basis of therapeutics. 10th ed. New York: McGraw-Hill Co., 2001

    Google Scholar 

  14. Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron 1976; 16(1): 31–41

    Article  PubMed  CAS  Google Scholar 

  15. Levey AS, Greene T, Kusek JW, et al., MDRD Study Group. A simplified equation to predict glomerular filtration rate from serum creatinine [abstract]. J Am Soc Nephrol 2000; 11: A0828

    Google Scholar 

  16. Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med 2009 May 5; 150(9): 604–12

    PubMed  Google Scholar 

  17. K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Am J Kidney Dis 2002 Feb; 39(2 Suppl. 1): S1–266

    Google Scholar 

  18. Coresh J, Auguste P. Reliability of GFR formulas based on serum creatinine, with special reference to the MDRD Study equation. Scand J Clin Lab Invest Suppl 2008; 241: 30–8

    Article  PubMed  Google Scholar 

  19. Katz S, Ford AB, Moskowitz RW, et al. Studies of illness in the aged. The index of ADL: a standardized measure of biological and psychosocial function. JAMA 1963 Sep 21; 185: 914–9

    Article  PubMed  CAS  Google Scholar 

  20. Rocca WA, Bonaiuto S, Lippi A, et al. Validation of the Hodkinson abbreviated mental test as a screening instrument for dementia in an Italian population. Neuroepidemiology 1992; 11(4–6): 288–95

    Article  PubMed  CAS  Google Scholar 

  21. PHS-HCF. International classification of diseases, 9th revision. Clinical modifications. Washington, DC: Public Health Service-Health Care Financing Administration, 1980

    Google Scholar 

  22. Charlson ME, Pompei P, Ales KL, et al. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987; 40(5): 373–83

    Article  PubMed  CAS  Google Scholar 

  23. Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 1992 Jun; 45(6): 613–9

    Article  PubMed  CAS  Google Scholar 

  24. Pahor M, Chrischilles EA, Guralnik JM, et al. Drug data coding and analysis in epidemiologic studies. Eur J Epidemiol 1994 Aug; 10(4): 405–11

    Article  PubMed  CAS  Google Scholar 

  25. Altman DG. Some common problems in medical research. Practical statistics for medical research. London: Chapman & Hall, 1997

    Google Scholar 

  26. Hanley JA, McNeil BJ. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 1982 Apr; 143(1): 29–36

    PubMed  CAS  Google Scholar 

  27. Jones CA, McQuillan GM, Kusek JW, et al. Serum creatinine levels in the US population: third National Health and Nutrition Examination Survey. Am J Kidney Dis 1998 Dec; 32(6): 992–9

    Article  PubMed  CAS  Google Scholar 

  28. Hanlon JT, Aspinall SL, Semla TP, et al. Consensus guidelines for oral dosing of primarily renally cleared medications in older adults. J Am Geriatr Soc 2009 Feb; 57(2): 335–40

    Article  PubMed  Google Scholar 

  29. Corsonello A, Pedone C, Corica F, et al. Concealed renal failure and adverse drug reactions in older patients with type 2 diabetes mellitus. J Gerontol A Biol Sci Med Sci 2005 Sep; 60(9): 1147–51

    Article  PubMed  Google Scholar 

  30. Corsonello A, Pedone C, Corica F, et al. Estimating glomerular filtration rate might help to avoid hypoglycemia. J Am Geriatr Soc 2006 Sep; 54(9): 1469–70

    Article  PubMed  Google Scholar 

  31. Farrell B, Pottie K, Hogg W. Case report: adverse drug reactions in unrecognized kidney failure. Can Fam Physician 2004 Oct; 50: 1385–7

    PubMed  Google Scholar 

  32. Landi F, Onder G, Gambassi G, et al. Body mass index and mortality among hospitalized patients. Arch Intern Med 2000 Sep 25; 160(17): 2641–4

    Article  PubMed  CAS  Google Scholar 

  33. Onder G, Landi F, Volpato S, et al. Serum cholesterol levels and in-hospital mortality in the elderly. Am J Med 2003 Sep; 115(4): 265–71

    Article  PubMed  CAS  Google Scholar 

  34. 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 Apr; 55(4): 648–59

    Article  PubMed  Google Scholar 

  35. White SL, Polkinghorne KR, Atkins RC, 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. Am J Kidney Dis 2010 Apr; 55(4): 660–70

    Article  PubMed  Google Scholar 

  36. 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 60mL/min/1.73m2. Am J Kidney Dis 2010 Sep; 56(3): 486–95

    Article  PubMed  Google Scholar 

  37. El-Ghoul B, Elie C, Sqalli T, et al. Nonprogressive kidney dysfunction and outcomes in older adults with chronic kidney disease. J Am Geriatr Soc 2009 Dec; 57(12): 2217–23

    Article  PubMed  Google Scholar 

  38. Douville P, Martel AR, Talbot J, et al. Impact of age on glomerular filtration estimates. Nephrol Dial Transplant 2009 Jan; 24(1): 97–103

    Article  PubMed  Google Scholar 

  39. Corsonello A, Pedone C, Incalzi RA. Age-related pharmacokinetic and pharmacodynamic changes and related risk of adverse drug reactions. Curr Med Chem 2010; 17(6): 571–84

    Article  PubMed  CAS  Google Scholar 

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Acknowledgements

The GIFA is partially supported by a grant (94000402) from the Italian National Research Council, Rome, Italy. The GIFA is a research group of the Italian Society of Gerontology and Geriatrics (SIGG: Società Italiana di Gerontologia e Geriatria) — the Italian Foundation for Research on Aging (FIRI-ONLUS: Fondazione Italiana per la Ricerca sull’Invecchiamento). A complete list of the GIFA investigators has been published previously.[10]

All authors declare that they have no conflict of interest to disclose.

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Corsonello, A., Pedone, C., Lattanzio, F. et al. Association between Glomerular Filtration Rate and Adverse Drug Reactions in Elderly Hospitalized Patients. Drugs Aging 28, 379–390 (2011). https://doi.org/10.2165/11588280-000000000-00000

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