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Association between increased mortality rate and antibiotic dose adjustment in intensive care unit patients with renal impairment

  • Pharmacoepidemiology and Prescription
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Abstract

Purpose

Adjusting the antibiotic dose based on an estimation of the glomerular filtration rate (eGFR) may result in subdosing, which may actually be significantly more problematic for intensive care unit (ICU) patients than not adjusting the dose. The aim of this study was to assess the outcomes of antibiotic dose adjustment in ICU patients with renal impairment.

Methods

A retrospective cohort study was conducted in adult patients admitted to an ICU of a Brazilian hospital from January 2014 to December 2015. The eGFR was determined using Cockcroft–Gault and Modified Diet in Renal Disease equations for each day of hospitalization. Treatment failure was defined based on the clinical, laboratory, and radiological criteria.

Results

A total of 126 patients were assessed to meet the inclusion criteria and subsequently enrolled in the study (19.9% of patients admitted to the ICU during the study period). Of the 168 opportunities for dose adjustment, 99 (58.9%) adjustments were made. The mean eGFR in the group with dose adjustment was lower than that in the group without dose adjustment (38.5 vs. 40.7 mL/min/1.73 m2, respectively). The treatment failure rate among patients with dose adjustment and those treated with the usual dose was 59.3 and 38.9%, respectively (p = 0.023), and the mortality rates in the respective groups were 74.1 and 55.5% (p = 0.033). An association between dose adjustment and treatment failure/mortality rates was also observed in the multivariate analysis including the prognostic score.

Conclusions

In ICU patients with renal impairment, adjustments in antibiotic dose based on eGFR, significantly increased the risk of treatment failure and death.

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References

  1. Barrasa-Villar JI, Aibar-Remon C, Prieto-Andres P, Mareca-Donate R, Moliner-Lahoz J (2017) Impact on morbidity, mortality, and length of stay of hospital-acquired infections by resistant microorganisms. Clin Infect Dis 65(4):644–652. https://doi.org/10.1093/cid/cix411

    Article  PubMed  Google Scholar 

  2. Garcia-Lamberechts EJ, Gonzalez-Del Castillo J, Hormigo-Sanchez AI, Nunez-Orantos MJ, Candel FJ, Martin-Sanchez FJ (2017) Factors predicting failure in empirical antibiotic treatment. An Sist Sanit Navar 40(1):119–130. https://doi.org/10.23938/ASSN.0011

    Article  CAS  PubMed  Google Scholar 

  3. Denny KJ, Cotta MO, Parker SL, Roberts JA, Lipman J (2016) The use and risks of antibiotics in critically ill patients. Expert Opin Drug Saf 15(5):667–678. https://doi.org/10.1517/14740338.2016.1164690

    Article  CAS  PubMed  Google Scholar 

  4. Jager NG, van Hest RM, Lipman J, Taccone FS, Roberts JA (2016) Therapeutic drug monitoring of anti-infective agents in critically ill patients. Expert Rev Clin Pharmacol 9 (7):961-979. https://doi.org/10.1586/17512433.2016.1172209

  5. Tasa T, Metsvaht T, Kalamees R, Vilo J, Lutsar I (2017) DosOpt: a tool for personalized Bayesian dose adjustment of vancomycin in neonates. Ther Drug Monit 39(6):604–613. https://doi.org/10.1097/FTD.0000000000000456

    Article  CAS  PubMed  Google Scholar 

  6. Mouton JW, Muller AE, Canton R, Giske CG, Kahlmeter G, Turnidge J (2018) MIC-based dose adjustment: facts and fables. J Antimicrob Chemother 73(3):564–568. https://doi.org/10.1093/jac/dkx427

  7. van Hasselt JG, Schellens JH, Beijnen JH, Huitema AD (2014) Design of informative renal impairment studies: evaluation of the impact of design stratification on bias, precision and dose adjustment error. Investig New Drugs 32(5):913–927. https://doi.org/10.1007/s10637-014-0103-8

  8. Sharif-Askari FS, Syed Sulaiman SA, Saheb Sharif-Askari N, Al Sayed Hussain A (2014) Development of an adverse drug reaction risk assessment score among hospitalized patients with chronic kidney disease. PLoS One 9(4):e95991. https://doi.org/10.1371/journal.pone.0095991

    Article  CAS  PubMed  Google Scholar 

  9. Elinder CG, Barany P, Heimburger O (2014) The use of estimated glomerular filtration rate for dose adjustment of medications in the elderly. Drugs Aging 31(7):493–499. https://doi.org/10.1007/s40266-014-0187-z

    Article  CAS  PubMed  Google Scholar 

  10. Surana S, Kumar N, Vasudeva A, Shaikh G, Jhaveri KD, Shah H, Malieckal D, Fogel J, Sidhu G, Rubinstein S (2017) Awareness and knowledge among internal medicine house-staff for dose adjustment of commonly used medications in patients with CKD. BMC Nephrol 18(1):26. https://doi.org/10.1186/s12882-017-0443-7

    Article  PubMed  PubMed Central  Google Scholar 

  11. Martin JH, Fay MF, Udy A, Roberts J, Kirkpatrick C, Ungerer J, Lipman J (2011) Pitfalls of using estimations of glomerular filtration rate in an intensive care population. Intern Med J 41(7):537–543. https://doi.org/10.1111/j.1445-5994.2009.02160.x

    Article  CAS  PubMed  Google Scholar 

  12. Bicalho MD, Soares DB, Botoni FA, Reis AM, Martins MA (2015) Drug-induced nephrotoxicity and dose adjustment recommendations: agreement among four drug information sources. Int J Environ Res Public Health 12(9):11227–11240. https://doi.org/10.3390/ijerph120911227

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Kumar BV, Mohan T (2017) Retrospective comparison of estimated GFR using 2006 MDRD, 2009 CKD-EPI and Cockcroft–Gault with 24 hour urine creatinine clearance. J Clin Diagn Res 11(5):BC09–BC12. https://doi.org/10.7860/JCDR/2017/25124.9889

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Delanaye P, Guerber F, Scheen A, Ellam T, Bouquegneau A, Guergour D, Mariat C, Pottel H (2017) Discrepancies between the Cockcroft-gault and chronic kidney disease epidemiology (CKD-EPI) equations: implications for refining drug dosage adjustment strategies. Clin Pharmacokinet 56(2):193–205. https://doi.org/10.1007/s40262-016-0434-z

    Article  PubMed  Google Scholar 

  15. Karsch-Volk M, Schmid E, Wagenpfeil S, Linde K, Heemann U, Schneider A (2013) Kidney function and clinical recommendations of drug dose adjustment in geriatric patients. BMC Geriatr 13:92. https://doi.org/10.1186/1471-2318-13-92

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Khanal A, Peterson GM, Castelino RL, Jose MD (2014) Renal drug dosing recommendations: evaluation of product information for brands of the same drug. Intern Med J 44(6):591–596. https://doi.org/10.1111/imj.12446

    Article  CAS  PubMed  Google Scholar 

  17. Brown DL, Masselink AJ, Lalla CD (2013) Functional range of creatinine clearance for renal drug dosing: a practical solution to the controversy of which weight to use in the Cockcroft–Gault equation. Ann Pharmacother 47(7-8):1039–1044. https://doi.org/10.1345/aph.1S176

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  Google Scholar 

  19. Levey AS, Coresh J, Greene T, Stevens LA, Zhang YL, Hendriksen S, Kusek JW, Van Lente F, Chronic Kidney Disease Epidemiology C (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(4):247–254

    Article  CAS  PubMed  Google Scholar 

  20. Truven Health Analytics, Inc. (2016) Micromedex® 2.0. Truven Health Analytics, Inc. Greenwood Village http://www.micromedexsolutions.com

  21. American Pharmacists Association (2015). Drug information handbook, 24th edn. Lexi-Comp, Ohio State University, Columbus

  22. Ismail B, Shafei MN, Harun A, Ali S, Omar M, Deris ZZ (2017) Predictors of polymyxin B treatment failure in Gram-negative healthcare-associated infections among critically ill patients. J Microbiol Immunol Infect. https://doi.org/10.1016/j.jmii.2017.03.007

  23. Sanchez Garcia M (2009) Early antibiotic treatment failure. Int J Antimicrob Agents 34[Suppl 3]:S14–S19. https://doi.org/10.1016/S0924-8579(09)70552-7

    Article  CAS  PubMed  Google Scholar 

  24. Silva Junior JM, Malbouisson LM, Nuevo HL, Barbosa LG, Marubayashi LY, Teixeira IC, Nassar Junior AP, Carmona MJ, Silva IF, Auler Junior JO, Rezende E (2010) Applicability of the simplified acute physiology score (SAPS 3) in Brazilian hospitals. Rev Bras Anestesiol 60(1):20–31

    Article  PubMed  Google Scholar 

  25. Sunder S, Jayaraman R, Mahapatra HS, Sathi S, Ramanan V, Kanchi P, Gupta A, Daksh SK, Ram P (2014) Estimation of renal function in the intensive care unit: the covert concepts brought to light. J Intensive Care 2(1):31. https://doi.org/10.1186/2052-0492-2-31

    Article  PubMed  PubMed Central  Google Scholar 

  26. Zander J, Dobbeler G, Nagel D, Maier B, Scharf C, Huseyn-Zada M, Jung J, Frey L, Vogeser M, Zoller M (2016) Piperacillin concentration in relation to therapeutic range in critically ill patients—a prospective observational study. Crit Care 20:79. https://doi.org/10.1186/s13054-016-1255-z

    Article  PubMed  PubMed Central  Google Scholar 

  27. Roberts JA, Lipman J (2009) Pharmacokinetic issues for antibiotics in the critically ill patient. Crit Care Med 37(3):840–851; quiz 859. https://doi.org/10.1097/CCM.0b013e3181961bff

    Article  CAS  PubMed  Google Scholar 

  28. Eppenga WL, Kramers C, Derijks HJ, Wensing M, Wetzels JF, De Smet PA (2016) Drug therapy management in patients with renal impairment: how to use creatinine-based formulas in clinical practice. Eur J Clin Pharmacol 72(12):1433–1439. https://doi.org/10.1007/s00228-016-2113-2

  29. Charmillon A, Novy E, Agrinier N, Leone M, Kimmoun A, Levy B, Demore B, Dellamonica J, Pulcini C (2016) The ANTIBIOPERF study: a nationwide cross-sectional survey about practices for beta-lactam administration and therapeutic drug monitoring among critically ill patients in France. Clin Microbiol Infect 22(7):625–631. https://doi.org/10.1016/j.cmi.2016.04.019

    Article  CAS  PubMed  Google Scholar 

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Funding

No funding was received.

Author information

Authors and Affiliations

Authors

Contributions

MS Camargo was responsible for the study design, data analysis, and manuscript writing. S Mistro and MG Oliveira were responsible for the manuscript writing and data analysis. LC Passos supervised the study and was responsible for writing the manuscript.

Corresponding author

Correspondence to Marianne Silveira Camargo.

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Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. For this type of study formal consent is not required. The study was approved by the Research Ethics Committee at Multidisciplinary Institute of Health, Federal University of Bahia, Vitória da Conquista, Brazil, with number (CAAE): 52721616.6.0000.5556.

Datasets

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Camargo, M.S., Mistro, S., Oliveira, M.G. et al. Association between increased mortality rate and antibiotic dose adjustment in intensive care unit patients with renal impairment. Eur J Clin Pharmacol 75, 119–126 (2019). https://doi.org/10.1007/s00228-018-2565-7

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  • DOI: https://doi.org/10.1007/s00228-018-2565-7

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