Literature DB >> 24559594

Development of a urinary-specific antibiogram for gram-negative isolates: impact of patient risk factors on susceptibility.

Nicole Rabs1, Sarah M Wieczorkiewicz2, Michael Costello3, Ina Zamfirova4.   

Abstract

BACKGROUND: Traditional antibiograms guide clinicians in selecting appropriate empiric antimicrobials, but they lack data on syndrome/disease-specific susceptibility, isolate location, polymicrobial infections, and patient risk factors. The aim of this study was to develop a urinary-specific antibiogram and to evaluate the impact of risk factors on antimicrobial susceptibility.
METHODS: This retrospective descriptive study used culture and susceptibility data from January 1 to December 31, 2012. A urinary antibiogram specific for Escherichia coli (EC), Proteus mirabilis (PM), Klebsiella pneumoniae (KP), and Pseudomonas aeruginosa (PA) was developed. Urinary and standard antibiogram susceptibilities were compared. Urinary isolates were then stratified by risk factors-residence before admission, age, systemic antimicrobial use for ≤30 days, hospitalization for ≤30 days, and hospital unit-to determine the impact on antimicrobial susceptibility.
RESULTS: There were 2,284 urinary isolate encounters. Overall antimicrobial susceptibility was increased, and the prevalence of extended-spectrum β-lactamase-producing isolates was significantly greater (KP, 14% vs 7% [P = .001]; EC, 13% vs 9% [P < .001]; PM, 18% vs 10% [P = .004]) in the urinary antibiogram vs the standard antibiogram. Health care facility residence had the greatest impact on susceptibility for all urinary isolates, especially on fluoroquinolone susceptibility for EC and PM.
CONCLUSIONS: Using a syndromic antibiogram and incorporating patient risk factors into susceptibility data may be more useful in guiding clinicians in selecting more appropriate empiric therapy.
Copyright © 2014 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Mosby, Inc. All rights reserved.

Entities:  

Keywords:  Antimicrobial resistance; Urinary tract infection

Mesh:

Substances:

Year:  2014        PMID: 24559594     DOI: 10.1016/j.ajic.2013.11.004

Source DB:  PubMed          Journal:  Am J Infect Control        ISSN: 0196-6553            Impact factor:   2.918


  3 in total

1.  Prevalence of Antibiotic Resistance Over Time in a Third-Level University Hospital.

Authors:  Vincenzo Scaglione; Mariaconcetta Reale; Chiara Davoli; Maria Mazzitelli; Francesca Serapide; Rosaria Lionello; Valentina La Gamba; Paolo Fusco; Andrea Bruni; Daniela Procopio; Eugenio Garofalo; Federico Longhini; Nadia Marascio; Cinzia Peronace; Aida Giancotti; Luigia Gallo; Giovanni Matera; Maria Carla Liberto; Bruno Mario Cesana; Chiara Costa; Enrico Maria Trecarichi; Angela Quirino; Carlo Torti
Journal:  Microb Drug Resist       Date:  2021-12-15       Impact factor: 2.706

2.  Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data--The Influence of Different Parameters in a Routine Clinical Microbiology Laboratory.

Authors:  Rebekka Kohlmann; Sören G Gatermann
Journal:  PLoS One       Date:  2016-01-27       Impact factor: 3.240

Review 3.  Developmental roadmap for antimicrobial susceptibility testing systems.

Authors:  Alex van Belkum; Till T Bachmann; Gerd Lüdke; Jan Gorm Lisby; Gunnar Kahlmeter; Allan Mohess; Karsten Becker; John P Hays; Neil Woodford; Konstantinos Mitsakakis; Jacob Moran-Gilad; Jordi Vila; Harald Peter; John H Rex; Wm Michael Dunne
Journal:  Nat Rev Microbiol       Date:  2019-01       Impact factor: 60.633

  3 in total

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