Intensive Care Medicine

, Volume 42, Issue 6, pp 1029–1039 | Cite as

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

  • Liesbet De Bus
  • Wouter Denys
  • Julie Catteeuw
  • Bram Gadeyne
  • Karel Vermeulen
  • Jerina Boelens
  • Geert Claeys
  • Jan J. De Waele
  • Johan Decruyenaere
  • Pieter O. Depuydt



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.


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.


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).


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


Beta-lactam antibiotics Antibiotic stewardship Multi-drug resistance De-escalation Information technology system 



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.

Compliance with ethical standards

Conflicts of interest

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

Supplementary material

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Supplementary material 1 (DOC 60 kb)
134_2016_4301_MOESM2_ESM.doc (57 kb)
Supplementary material 2 (DOC 57 kb)
134_2016_4301_MOESM3_ESM.doc (82 kb)
Supplementary material 3 (DOC 81 kb)
134_2016_4301_MOESM4_ESM.doc (83 kb)
Supplementary material 4 (DOC 83 kb)


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Copyright information

© Springer-Verlag Berlin Heidelberg and ESICM 2016

Authors and Affiliations

  • Liesbet De Bus
    • 1
  • Wouter Denys
    • 1
  • Julie Catteeuw
    • 1
  • Bram Gadeyne
    • 1
  • Karel Vermeulen
    • 2
  • Jerina Boelens
    • 3
  • Geert Claeys
    • 3
  • Jan J. De Waele
    • 1
  • Johan Decruyenaere
    • 1
  • Pieter O. Depuydt
    • 1
    • 4
  1. 1.Department of Critical Care MedicineGhent University HospitalGhentBelgium
  2. 2.Department of Mathematical Modelling, Statistics and BioinformaticsGhent UniversityGhentBelgium
  3. 3.Department of Laboratory MedicineGhent University Hospital9000 GhentBelgium
  4. 4.Heymans Institute of PharmacologyGhent UniversityGhentBelgium

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