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Resistance Mechanisms in Pseudomonas aeruginosa and Other Nonfermentative Gram‐Negative Bacteria

Hancock, Robert E. W.·1998·Clinical Infectious Diseases

Abstract

Nonfermentative gram-negative bacilli are still a major concern in compromised individuals. By far the most important of these organisms is Pseudomonas aeruginosa, although Acinetobacter baumannii (previously Acinetobacter calcoaceticus), Stenotrophomonas maltophilia (previously Pseudomonas and Xanthomonas maltophilia), and Burkholderia cepacia (previously Pseudomonas cepacia) are also of substantative concern because of their similar high intrinsic resistances to antibiotics. The basis for the high intrinsic resistance of these organisms is the lower outer-membrane permeability of these species, coupled with secondary resistance mechanisms such as an inducible cephalosporinase or antibiotic efflux pumps, which take advantage of low outer-membrane permeability. Even a small change in antibiotic susceptibility of these organisms can result in an increase in the MIC of a drug to a level that is greater than the clinically achievable level. In this review, the major mechanisms of resistance observed in the laboratory and clinic are summarized.

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Metadata

Authors
Hancock, R. E. W.
Venue
Clinical Infectious Diseases
Published
1998-08
Volume
27
Issue
s1
Pages
S93-S99
ISSN
  • 1058-4838 (ISSN-L)
  • 1537-6591
OpenAlex
W2111839343
Cited by
583
References
0
FWCI
12.06
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Resistance Mechanisms in Pseudomonas aeruginosa and Other Nonfermentative Gram‐Negative Bacteria. https://app.cochat.ai/papers/10.1086/514909
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Hancock, R. E. W. (1998). Resistance Mechanisms in Pseudomonas aeruginosa and Other Nonfermentative Gram‐Negative Bacteria. Clinical Infectious Diseases. https://doi.org/10.1086/514909

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.