Literature DB >> 18426346

Outbreak of resistant Pseudomonas aeruginosa infections during a quarterly cycling antibiotic regimen.

Traci L Hedrick1, Alison S Schulman, Shannon T McElearney, Robert L Smith, Brian R Swenson, Heather L Evans, Jonathon D Truwit, W Michael Scheld, Robert G Sawyer.   

Abstract

BACKGROUND: Antibiotic cycling or rotation of antimicrobial agent classes has been proposed to combat antimicrobial resistance.
METHODS: A prospective cohort study was conducted in a medical intensive care unit (ICU) of a university hospital between December 1, 2000, and September 30, 2002, as part of a three-center trial under the aegis of the U.S. Centers for Disease Control and Prevention. Patients admitted to the medical ICU for > 48 h were enrolled, and demographic and microbiological data were collected until discharge or death. Baseline data were collected for four months (12/1/00 to 3/31/01) and compared with data collected after institution of a quarterly cycling regimen (cycle order: Cefepime, ciprofloxacin, piperacillin-tazobactam, imipenem-cilastatin) for the empiric treatment of gram-negative infections (4/01/01 to 9/30/02).
RESULTS: Of 1,074 consecutive admissions, 301 were enrolled, 59 during baseline and 242 during the cycling periods. An outbreak of multi-drug resistant Pseudomonas aeruginosa followed cycle 2 (cefepime), coinciding with cycles 3 and 4 (ciprofloxacin and piperacillin-tazobactam) (80.0 and 73.7 vs. 37.3 isolates/100 patients enrolled for cycles 3/4 and baseline, respectively; p = 0.04). Acinetobacter spp. were isolated less frequently during the cycling periods (15.3 vs. 1.2 isolates/100 patients for baseline and cycling periods, respectively; p > or = 0.01). The crude hospital mortality rate was similar (24/59 [41%] baseline vs. 73/242 [30%] cycling; p = 0.16) between periods. However, the percentage of patients admitted to the medical ICU who subsequently acquired an infection followed by in-hospital death was higher at baseline than during cycling: 15/59 (25.4%) vs. 33/242 (13.6%)(p = 0.04).
CONCLUSIONS: In this study, the cycling strategy was not definitively associated with beneficial changes in unit epidemiology and in fact may have contributed to an outbreak of multi-drug resistant P. aeruginosa.

Entities:  

Mesh:

Substances:

Year:  2008        PMID: 18426346     DOI: 10.1089/sur.2006.102

Source DB:  PubMed          Journal:  Surg Infect (Larchmt)        ISSN: 1096-2964            Impact factor:   2.150


  13 in total

1.  Imperfect drug penetration leads to spatial monotherapy and rapid evolution of multidrug resistance.

Authors:  Stefany Moreno-Gamez; Alison L Hill; Daniel I S Rosenbloom; Dmitri A Petrov; Martin A Nowak; Pleuni S Pennings
Journal:  Proc Natl Acad Sci U S A       Date:  2015-05-18       Impact factor: 11.205

2.  Strategies to enhance rational use of antibiotics in hospital: a guideline by the German Society for Infectious Diseases.

Authors:  K de With; F Allerberger; S Amann; P Apfalter; H-R Brodt; T Eckmanns; M Fellhauer; H K Geiss; O Janata; R Krause; S Lemmen; E Meyer; H Mittermayer; U Porsche; E Presterl; S Reuter; B Sinha; R Strauß; A Wechsler-Fördös; C Wenisch; W V Kern
Journal:  Infection       Date:  2016-06       Impact factor: 3.553

Review 3.  Overcoming drug resistance in multi-drug resistant cancers and microorganisms: a conceptual framework.

Authors:  Benjamin S Avner; Arsenio M Fialho; Ananda M Chakrabarty
Journal:  Bioengineered       Date:  2012-07-03       Impact factor: 3.269

4.  Impact of a Multimodal Antimicrobial Stewardship Program on Pseudomonas aeruginosa Susceptibility and Antimicrobial Use in the Intensive Care Unit Setting.

Authors:  Douglas Slain; Arif R Sarwari; Karen O Petros; Richard L McKnight; Renee B Sager; Charles J Mullett; Alison Wilson; John G Thomas; Kathryn Moffett; H Carlton Palmer; Harakh V Dedhia
Journal:  Crit Care Res Pract       Date:  2011-05-19

5.  The effects of antibiotic cycling and mixing on acquisition of antibiotic resistant bacteria in the ICU: A post-hoc individual patient analysis of a prospective cluster-randomized crossover study.

Authors:  Pleun J van Duijn; Walter Verbrugghe; Philippe G Jorens; Fabian Spöhr; Dirk Schedler; Maria Deja; Andreas Rothbart; Djillali Annane; Christine Lawrence; Matjaz Jereb; Katja Seme; Franc Šifrer; Viktorija Tomič; Francisco Estevez; Jandira Carneiro; Stephan Harbarth; Marc J M Bonten
Journal:  PLoS One       Date:  2022-05-03       Impact factor: 3.752

6.  Evaluation of a Mixing versus a Cycling Strategy of Antibiotic Use in Critically-Ill Medical Patients: Impact on Acquisition of Resistant Microorganisms and Clinical Outcomes.

Authors:  Nazaret Cobos-Trigueros; Mar Solé; Pedro Castro; Jorge Luis Torres; Mariano Rinaudo; Elisa De Lazzari; Laura Morata; Cristina Hernández; Sara Fernández; Alex Soriano; José María Nicolás; Josep Mensa; Jordi Vila; José Antonio Martínez
Journal:  PLoS One       Date:  2016-03-16       Impact factor: 3.240

7.  Antibiotic Cycling and Antibiotic Mixing: Which One Best Mitigates Antibiotic Resistance?

Authors:  Robert Eric Beardmore; Rafael Peña-Miller; Fabio Gori; Jonathan Iredell
Journal:  Mol Biol Evol       Date:  2017-04-01       Impact factor: 16.240

8.  Resource competition may lead to effective treatment of antibiotic resistant infections.

Authors:  Antonio L C Gomes; James E Galagan; Daniel Segrè
Journal:  PLoS One       Date:  2013-12-13       Impact factor: 3.240

9.  Cycling empirical antibiotic therapy in hospitals: meta-analysis and models.

Authors:  Pia Abel zur Wiesch; Roger Kouyos; Sören Abel; Wolfgang Viechtbauer; Sebastian Bonhoeffer
Journal:  PLoS Pathog       Date:  2014-06-26       Impact factor: 6.823

10.  Antibiotic rotation strategies to reduce antimicrobial resistance in Gram-negative bacteria in European intensive care units: study protocol for a cluster-randomized crossover controlled trial.

Authors:  Pleun J van Duijn; Marc J M Bonten
Journal:  Trials       Date:  2014-07-10       Impact factor: 2.279

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.