Emergence of antimicrobial resistance to Pseudomonas aeruginosa in the intensive care unit: association with the duration of antibiotic exposure and mode of administration

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Abstract

Background

Antibiotics are frequently used in intensive care units (ICUs), and their use is associated with the emergence of bacterial resistance to antibiotics. The aim of this study was to investigate the association between the emergence of Pseudomonas aeruginosa resistance and the duration of antibiotic exposure or mode of administration in an ICU unit.

Methods

A 4-year cohort study of intensive care unit was performed in patients with P. aeruginosa isolates from clinical specimens, initially susceptible to the investigated antibiotics (piperacillin/tazobactam, ceftazidime, ciprofloxacin, meropenem and amikacin). Odds ratios (ORs) with 95% confidence interval (95% CI) of emergence of resistance were calculated using logistic regression analysis for various exposure periods to antibiotics (1–3, 4–7, 8–15 and >15 days) relative to no exposure with adjustment for age, sex, Simplified Acute Physiology Score 3 (SAPS 3) and length of stay. ORs on the emergence of P. aeruginosa resistance were also calculated for the various modes of administration.

Results

Included were 187 patients [mean age 61 years, 69% male, mean SAPS 3 score (SD): 59 (12.3)]. None of the antibiotics investigated showed the emergence of resistance within 1–3 days. Significant meropenem resistance emerged within 8–15 days [OR 79.1 (14.9–421.0)] after antibiotic exposure unlike other antibiotics (>15 days). No difference was observed between intermittent and extended administration of meropenem and between beta-lactam mono- or combined therapy.

Conclusions

Use of meropenem was associated with the emergence of resistance as soon as 8 days after exposure to the antibiotic.

Related collections

Most cited references 14

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SAPS 3—From evaluation of the patient to evaluation of the intensive care unit. Part 2: Development of a prognostic model for hospital mortality at ICU admission

Rui P Moreno, Philipp G H Metnitz, Eduardo Almeida … (2005)

Objective To develop a model to assess severity of illness and predict vital status at hospital discharge based on ICU admission data. Design Prospective multicentre, multinational cohort study. Patients and setting A total of 16,784 patients consecutively admitted to 303 intensive care units from 14 October to 15 December 2002. Measurements and results ICU admission data (recorded within ±1 h) were used, describing: prior chronic conditions and diseases; circumstances related to and physiologic derangement at ICU admission. Selection of variables for inclusion into the model used different complementary strategies. For cross-validation, the model-building procedure was run five times, using randomly selected four fifths of the sample as a development- and the remaining fifth as validation-set. Logistic regression methods were then used to reduce complexity of the model. Final estimates of regression coefficients were determined by use of multilevel logistic regression. Variables selection and weighting were further checked by bootstraping (at patient level and at ICU level). Twenty variables were selected for the final model, which exhibited good discrimination (aROC curve 0.848), without major differences across patient typologies. Calibration was also satisfactory (Hosmer-Lemeshow goodness-of-fit test Ĥ=10.56, p=0.39, Ĉ=14.29, p=0.16). Customised equations for major areas of the world were computed and demonstrate a good overall goodness-of-fit. Conclusions The SAPS 3 admission score is able to predict vital status at hospital discharge with use of data recorded at ICU admission. Furthermore, SAPS 3 conceptually dissociates evaluation of the individual patient from evaluation of the ICU and thus allows them to be assessed at their respective reference levels. Electronic Supplementary Material Electronic supplementary material is included in the online fulltext version of this article and accessible for authorised users: http://dx.doi.org/10.1007/s00134-005-2763-5

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Emergence of antibiotic-resistant Pseudomonas aeruginosa: comparison of risks associated with different antipseudomonal agents.

Yehuda Carmeli, Nicolas Troillet, George Eliopoulos … (1999)

Pseudomonas aeruginosa is a leading cause of nosocomial infections. The risk of emergence of antibiotic resistance may vary with different antibiotic treatments. To compare the risks of emergence of resistance associated with four antipseudomonal agents, ciprofloxacin, ceftazidime, imipenem, and piperacillin, we conducted a cohort study, assessing relative risks for emergence of resistant P. aeruginosa in patients treated with any of these drugs. A total of 271 patients (followed for 3,810 days) with infections due to P. aeruginosa were treated with the study agents. Resistance emerged in 28 patients (10.2%). Adjusted hazard ratios for the emergence of resistance were as follows: ceftazidime, 0.7 (P = 0.4); ciprofloxacin, 0.8 (P = 0.6); imipenem, 2.8 (P = 0.02); and piperacillin, 1.7 (P = 0.3). Hazard ratios for emergence of resistance to each individual agent associated with treatment with the same agent were as follows: ceftazidime, 0.8 (P = 0.7); ciprofloxacin, 9.2 (P = 0.04); imipenem, 44 (P = 0.001); and piperacillin, 5.2 (P = 0.01). We concluded that there were evident differences among antibiotics in the likelihood that their use would allow emergence of resistance in P. aeruginosa. Ceftazidime was associated with the lowest risk, and imipenem had the highest risk.

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Optimization of meropenem minimum concentration/MIC ratio to suppress in vitro resistance of Pseudomonas aeruginosa.

Keith Poole, Meaghan E. Coyle, N Schilling … (2005)

Suppression of resistance in a dense Pseudomonas aeruginosa population has previously been shown with optimized quinolone exposures. However, the relevance to beta-lactams is unknown. We investigated the bactericidal activity of meropenem and its propensity to suppress P. aeruginosa resistance in an in vitro hollow-fiber infection model (HFIM). Two isogenic strains of P. aeruginosa (wild type and an AmpC stably derepressed mutant [MIC = 1 mg/liter]) were used. An HFIM inoculated with approximately 1 x 10(8) CFU/ml of bacteria was subjected to various meropenem exposures. Maintenance doses were given every 8 h to simulate the maximum concentration achieved after a 1-g dose in all regimens, but escalating unbound minimum concentrations (C(min)s) were simulated with different clearances. Serial samples were obtained over 5 days to quantify the meropenem concentrations, the total bacterial population, and subpopulations with reduced susceptibilities to meropenem (>3x the MIC). For both strains, a significant bacterial burden reduction was seen with all regimens at 24 h. Regrowth was apparent after 3 days, with the C(min)/MIC ratio being or = 6.2 or by adding tobramycin to meropenem (C(min)/MIC = 1.7). Investigations that were longer than 24 h and that used high inocula may be necessary to fully evaluate the relationship between drug exposures and the likelihood of resistance suppression. These results suggest that the C(min)/MIC of meropenem can be optimized to suppress the emergence of non-plasmid-mediated P. aeruginosa resistance. Our in vitro data support the use of an extended duration of meropenem infusion for the treatment of severe nosocomial infections in combination with an aminoglycoside.

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Author and article information

Contributors

Erlangga Yusuf:

ORCID: http://orcid.org/0000-0003-4779-2191

+32 (0)3 821 37 87 , angga.yusuf@gmail.com

Bruno Van Herendael: bruno.vanherendael@gza.be

Walter Verbrugghe: Walter.Verbrugghe@uza.be

Margareta Ieven: greet.ieven@uza.be

Emiel Goovaerts: Emiel.Goovaerts@uza.be

Kristof Bergs: Kristof.Bergs@uza.be

Kristien Wouters: kristien.wouters@uza.be

Philippe G. Jorens: Philippe.Jorens@uza.be

Herman Goossens: Herman.Goossens@uza.be

Journal

Journal ID (nlm-ta): Ann Intensive Care

Journal ID (iso-abbrev): Ann Intensive Care

Title: Annals of Intensive Care

Publisher: Springer International Publishing (Cham )

ISSN (Electronic): 2110-5820

Publication date (Electronic): 29 June 2017

Publication date PMC-release: 29 June 2017

Publication date Collection: 2017

Volume: 7

Electronic Location Identifier: 72

Affiliations

[1 ]Department of Microbiology, Antwerp University Hospital (UZA), University of Antwerp, Wilrijkstraat 10, 2650 Edegem, Belgium

[2 ]Department of Intensive Care Medicine, Antwerp University Hospital (UZA), University of Antwerp, Wilrijkstraat 10, 2650 Edegem, Belgium

[3 ]Department of Hospital Hygiene and Infection Control, Antwerp University Hospital (UZA), University of Antwerp, Wilrijkstraat 10, 2650 Edegem, Belgium

[4 ]Department of Biostatistics, Antwerp University Hospital (UZA), University of Antwerp, Wilrijkstraat 10, 2650 Edegem, Belgium

[5 ]GZA Hospitals, Antwerp, Belgium

Author information

Erlangga Yusuf http://orcid.org/0000-0003-4779-2191

Article

Publisher ID: 296

DOI: 10.1186/s13613-017-0296-z

PMC ID: 5491427

PubMed ID: 28664350

SO-VID: 1c264324-370f-4091-b710-fd5cfb674889

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.