Log in

Impact of de-escalation of beta-lactam antibiotics on the emergence of antibiotic resistance in ICU patients: a retrospective observational study

  • Original
  • Published:
Intensive Care Medicine Aims and scope Submit manuscript

Abstract

Purpose

Antibiotic de-escalation is promoted to limit prolonged exposure to broad-spectrum antibiotics, but proof that it prevents the emergence of resistance is lacking. We evaluated determinants of antibiotic de-escalation in an attempt to assess whether the latter is associated with a lower emergence of antimicrobial resistance.

Methods

Antibiotic treatments, starting with empirical beta-lactam prescriptions, were prospectively documented during 2013 and 2014 in a tertiary intensive care unit (ICU) and categorized as continuation, de-escalation or escalation of the empirical antimicrobial treatment. Determinants of the de-escalation or escalation treatments were identified by multivariate logistic regression; the continuation category was used as the reference group. Using systematically collected diagnostic and surveillance cultures, we estimated the cumulative incidence of antimicrobial resistance following de-escalation or continuation of therapy, with adjustment for ICU discharge and death as competing risks.

Results

Of 478 anti-pseudomonal antibiotic prescriptions, 42 (9 %) were classified as escalation of the antimicrobial treatment and 121 (25 %) were classified as de-escalation, mainly through replacement of the originally prescribed antibiotics with those having a narrower spectrum. In multivariate analysis, de-escalation was associated with the identification of etiologic pathogens (p < 0.001). The duration of the antibiotic course in the ICU in de-escalated versus continued prescriptions was 8 (range 6–10) versus 5 (range 4–7) days, respectively (p < 0.001). Mortality did not differ between patients in the de-escalation and continuation categories. The cumulative incidence estimates of the emergence of resistance to the initial beta-lactam antibiotic on day 14 were 30.6 and 23.5 % for de-escalation and continuation, respectively (p = 0.22). For the selection of multi-drug resistant pathogens, these values were 23.5 (de-escalation) and 18.6 % (continuation) respectively (p = 0.35).

Conclusion

The emergence of antibiotic-resistant bacteria after exposure to anti-pseudomonal beta-lactam antibiotics was not lower following de-escalation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Canada)

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Dellinger RP, Levy MM, Rhodes A, Annane D, Gerlach H, Opal SM, Sevransky JE, Sprung CL, Douglas IS, Jaeschke R, Osborn TM, Nunnally ME, Townsend SR, Reinhart K, Kleinpell RM, Angus DC, Deutschman CS, Machado FR, Rubenfeld GD, Webb S, Beale RJ, Vincent J-L, Moreno R, The Surviving Sepsis Campaign Guidelines Committee including The Pediatric Subgroup (2013) Surviving Sepsis Campaign: International guidelines for management of severe sepsis and septic shock, 2012. Intensive Care Med 39:165–228

    Article  CAS  PubMed  Google Scholar 

  2. Dellit TH, Owens RC, McGowan JE, Gerding DN, Weinstein RA, Burke JP, Huskins WC, Paterson DL, Fishman NO, Carpenter CF, Brennan PJ, Billeter M, Hooton TM (2007) Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America guidelines for develo** an institutional program to enhance antimicrobial stewardship. Clin Infect Dis 44:159–177

    Article  PubMed  Google Scholar 

  3. Kollef MH (2001) Hospital-acquired pneumonia and de-escalation of antimicrobial treatment. Crit Care Med 29(7):1473–1475

    Article  CAS  PubMed  Google Scholar 

  4. Kollef MH (2001) Optimizing antibiotic therapy in the intensive care unit setting. Crit Care 5:189–195

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Niederman MS (2006) De-escalation therapy in ventilator-associated pneumonia. Curr Opin Crit Care 12:452–457

    Article  PubMed  Google Scholar 

  6. Silva BNG, Andriolo RB, Atallah AN, Salomao R (2013) De-escalation of antimicrobial treatment for adults with sepsis, severe sepsis or septic shock (review). Cochrane Database Systematic Rev 3:CD007934 doi:10.1002/14651858

  7. Tabah A, Cotta MO, Garnacho-Montero J, Schouten J, Roberts JA, Lipman J, Tacey M, Timsit JF, Leone M, Zahar JR, De Waele J, on behalf of the Working Group for Antimicrobial Use in the ICU (2015) A systematic review of the definitions, determinants and clinical outcomes of antimicrobial de-escalation in the intensive care unit. Clin Infect Dis. doi:10.1093/cid/civ1199

    PubMed  Google Scholar 

  8. Garnacho-Montero J, Escoresca-Ortega A, Fernandez-Delgado E (2015) Antibiotic de-escalation in the ICU: how is it best done? Curr Opin Infect Dis 28:193–198

    Article  CAS  PubMed  Google Scholar 

  9. Garnacho-Montero J, Gutiérrez-Pizarraya A, Escoresca-Ortega A, Corcia-Palomo Y, Fernandez-Delgado E, Herrera-Melero I, Ortiz-Leyba C, Marquez-Vacaro JA (2014) De-escalation of empirical therapy is associated with lower mortality in patients with severe sepsis and septic shock. Intensive Care Med 40:32–40

    Article  CAS  PubMed  Google Scholar 

  10. Knaak E, Cavalieri SJ, Elsasser GN, Preheim LC, Gonitzke A, Destache CJ (2013) Does antibiotic de-escalation for nosocomial pneumonia impact intensive care unit length of stay? Infect Dis Clin Pract 21(3):172–176

    Article  Google Scholar 

  11. Giantsou E, Liratzopoulos N, Efraimidou E, Panopoulou M, Alepopoulou E, Kartali-Ktenidou S, Manolas K (2007) De-escalation therapy rates are significantly higher by bronchoalveolar lavage than by tracheal aspirate. Intensive Care Med 33:1533–1540

    Article  PubMed  Google Scholar 

  12. Gonzalez L, Cravoisy A, Barraud D, Conrad M, Nace L, Lemarié J, Bollaert P-E, Gibot S (2013) Factors influencing the implementation of antibiotic de-escalation and impact of this strategy in critically ill patients. Crit Care 17:R140

    Article  PubMed  PubMed Central  Google Scholar 

  13. Mokart D, Slehofer G, Lambert J, Sannini A, Chow-Chine L, Brun J-P, Berger P, Duran S, Faucher M, Blanche J-L, Saillard C, Vey N, Leone M (2014) De-escalation of antimicrobial treatment in neutropenic patients with severe sepsis: results of an observational study. Intensive Care Med 40:41–49

    Article  CAS  PubMed  Google Scholar 

  14. Leone M, Bechis C, Baumstarck K, Lefrant J-Y, Albanèse J, Jaber S, Lepape A, Constantin J-M, Papazian L, Bruder N, Allaouchiche B, Bézulier K, Antonini F, Textoris J, Martin C, for the AZUREA network investigators (2014) De-escalation versus continuation of empirical antimicrobial treatment in severe sepsis: a multicenter non-blinded randomized noninferiority trial. Intensive Care Med 40:1399–1408

    Article  CAS  PubMed  Google Scholar 

  15. Steurbaut K, Colpaert K, Gadeyne B, Depuydt P, Vosters P, Danneels C, Benoit D, Decruyenaere J, De Turck F (2012) COSARA: integrated service platform for infection surveillance and antibiotic management in the ICU. J Med Syst 36:3765–3775

    Article  PubMed  Google Scholar 

  16. De Bus L, Diet G, Gadeyne B, Leroux-Roels I, Claeys G, Steurbaut K, Benoit D, De Turck F, Decruyenaere J, Depuydt P (2014) Validity analysis of a unique infection surveillance system in the intensive care unit by analysis of a data warehouse built through a workflow-integrated software application. J Hosp Infect 87:159–164

    Article  PubMed  Google Scholar 

  17. De Bus L, Saerens L, Gadeyne B, Boelens J, Claeys G, De Waele JJ, Benoit DD, Decruyenaere J, Depuydt PO (2014) Development of antibiotic treatment algorithms based on local ecology and respiratory surveillance cultures to restrict the use of broad-spectrum antimicrobial drugs in the treatment of hospital-acquired pneumonia in the intensive care unit: a retrospective analysis. Crit Care 18:R152

    Article  PubMed  PubMed Central  Google Scholar 

  18. Saag MS. Gilbert DN CH, Eliopoulos GM, Moellering RC (2012) The Sanford guide to antimicrobial therapy. 23rd edition of the Belgian/Luxembourg version 2012–2013. Antimicrobial Therapy Inc., Sperryville

  19. Magiorakos A-P, Srinivasan A, Carey RB, Carmeli Y, Falagas ME, Giske CG, Harbarth S, Hindler JF, Kahlmeter G, Olsson-Liljequist B, Paterson DL, Rice LB, Stelling J, Struelens MJ, Vatopoulos A, Weber JT, Monnet DL (2012) Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 18:268–281

    Article  CAS  PubMed  Google Scholar 

  20. R-GNOSIS (2011) Resistance in Gram-Negative Organisms: Studying Intervention Strategies. Available at: http://www.r-gnosis.eu/. Accessed 14 March 2016

  21. Andersen PK, Abildstrom SZ, Rosthoj S (2002) Competing risk as a multi-state model. Stat Methods Med Res 11:203–215

    Article  PubMed  Google Scholar 

  22. Pepe M, Mori M (1993) Kaplan-Meier, marginal or conditional probability curves in summarizing competing risk failure time data? Stat Med 12(8):737–751

    Article  CAS  PubMed  Google Scholar 

  23. Satagopan JM, Ben-Porat L, Berwick M, Robson M, Kutler D, Auerbach AD (2004) A note on competing risks in survival data analysis. Br J Cancer 91(4):1229–1235

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Gray RJ (1998) A class of k-sample tests for comparing the cumulative incidence of a competing risk. Ann Stat 16:1141–1154

    Article  Google Scholar 

  25. (2015) R Foundation for Statistical Computing. R: a language and environment for statistical computing (version 3.2.2). Available at: http://www.R-project.org

  26. cmprsk-package. Available at: https://cran.r-project.org/web/packages/cmprsk/cmprsk.pdf. Accessed 14 March 2016

  27. Morel J, Casoetto J, Jospé R, Aubert G, Terrana R, Dumont A, Molliex S, Auboyer C (2010) De-escalation as part of a global strategy of empiric antibiotherapy management. A retrospective study in a medico-surgical intensive care unit. Crit Care 14(6):R225

    Article  PubMed  PubMed Central  Google Scholar 

  28. De Waele JJ, Ravyts M, Depuydt P, Blot SI, Decruyenaere J, Vogelaers D (2010) De-escalation after empirical meropenem treatment in the intensive care unit: fiction or reality? J Crit Care 25:641–646

    Article  PubMed  Google Scholar 

  29. Álvarez-Lerma F, Alvarez B, Luque P, Ruiz F, Dominguez-Roldan J-M, Quintana E, Sanz-Rodriguez C, The ADANN Study Group (2006) Empiric broad-spectrum antibiotic therapy of nosocomial pneumonia in the intensive care unit: a prospective observational study. Crit Care 10:R78

    Article  PubMed  PubMed Central  Google Scholar 

  30. McCullough AR, Rathboneb J, Parekh S, Hoffmann TC, Del Mar CB (2015) Not in my backyard: a systematic review of clinicians’ knowledge and beliefs about antibiotic resistance. J Antimicrob Chemother 70:2465–2473

    Article  CAS  PubMed  Google Scholar 

  31. Joung MK, Lee JA, Moon SY, Cheong HS, Joo EJ, Ha YE, Sohn KM, Chung SM, Suh GY, Chung DR, Song JH, Peck KR (2011) Impact of de-escalation therapy on clinical outcomes for intensive care unit-acquired pneumonia. Crit Care 15(2):R79

    Article  PubMed  PubMed Central  Google Scholar 

  32. Armand-Lefèvre L, Angebault C, Barbier F, Hamelet E, Defrance G, Ruppé E, Bronchard R, Lepeule R, Lucet JC, El Mniai A, Wolff M, Montravers P, Plésiat P, Andremonta A (2013) Emergence of imipenem-resistant gram-negative bacilli in intestinal flora of intensive care patients. Antimicrob Agents Chemother 57(3):1488–1495

    Article  PubMed  PubMed Central  Google Scholar 

  33. Carlier M, Roberts JA, Stove V, Verstraete AG, Lipman J, De Waele JJ (2015) A simulation study reveals lack of pharmacokinetic/pharmacodynamic target attainment in de-escalated antibiotic therapy in critically ill patients. Antimicrob Agents Chemother 59(8):4689–4694

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Weiss E, Zahar JR, Lesprit P, Ruppe E, Leone M, Chastre J, Lucet JC, Paugam-Burtz C, Brun-Buisson C, Timsit JF, De-escalation study Group (2015) Elaboration of a consensual definition of de-escalation allowing a ranking of beta-lactams. Clin Microbiol Infect 21(7):649.e1–649.e10

    Article  CAS  Google Scholar 

  35. Madaras-Kelly K, Jones M, Remington R, Hill N, Huttner B, Samore M (2014) Development of an antibiotic spectrum score based on veterans affairs culture and susceptibility data for the purpose of measuring antibiotic de-escalation: a modified Delphi approach. Infect Control Hosp Epidemiol 35(9):1103–1113

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgments

This research project is funded by the IWT (Institute for the Promotion of Innovation through Science and Technology in Flanders) (project IWT–TBM COSARA–project number 060517). LDB received a Clinical Research Grant from Ghent University Hospital, Belgium (project number KW/1394/INT/001/001). JDW is a senior Clinical Investigator with the Research Foundation Flanders (FWO).

Authors' contributions

LDB and PD conceived the study, participated in its design and coordination, analyzed the data, and drafted the manuscript; WD, JC, LDB, KV, and BG performed data acquisition and analyses; WD, JC, BG, KV, JB, GC, JDW, and JD critically revised the manuscript for important intellectual content. All authors read and approved the final manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Liesbet De Bus.

Ethics declarations

Conflicts of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Additional information

Take-home message: The results of this study do not confirm the expected favorable effect of de-escalation of anti-pseudomonal beta-lactam antibiotic treatment on the selection of antimicrobial resistance. De-escalation should therefore not be considered to be a safe strategy underpinning an unlimited empirical use of broad-spectrum combination therapy. Future research to determine the most optimal de-escalation strategy and by extension the most optimal antibiotic strategy reducing overall antibiotic exposure and antimicrobial selection pressure is essential.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

De Bus, L., Denys, W., Catteeuw, J. et al. Impact of de-escalation of beta-lactam antibiotics on the emergence of antibiotic resistance in ICU patients: a retrospective observational study. Intensive Care Med 42, 1029–1039 (2016). https://doi.org/10.1007/s00134-016-4301-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00134-016-4301-z

Keywords

Navigation