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Antimicrobial Susceptibility Testing Methods for Bacterial Pathogens

  • Fred C. Tenover
Part of the Infectious Disease book series (ID)

Gone are the days when the antimicrobial susceptibility pattern of a bacterial isolate could be predicted simply on the basis of its species identifi cation. Although Streptococcus pyogenes isolates remain susceptible to penicillin, one has to continually ask – for how long? With the discovery of strains of Staphylococcus aureus that are highly resistant to vancomycin (1) and strains of Acinetobacter species that are pan resistant (2, 3), the role of antimicrobial susceptibility testing in guiding therapy for infectious diseases is becoming more and more important (4). Yet, ironically, many of these novel resistance phenotypes are not easily detected using the automated susceptibility testing methods so prevalent in today’s clinical laboratories (5–7). The ability of the clinical laboratory to detect emerging resistance profi les is often directly related to the extra efforts expanded to catch novel resistance mechanisms. Although resistant bacteria were common previously only in intensive care units of hospitals, multidrug resistance has become an issue among strains of community-acquired pathogens such as Salmonella, Shigella, and even Neisseria gonorrhoeae (8, 9). To complicate matters even further, resistant organisms that arise in the community are now also spreading into healthcare settings (10, 11). Therefore, it is imperative that changes in resistance patterns of a wide range of bacterial pathogens be monitored continually to ensure optimal treatment both of the individual patients and for maintaining the effi cacy of empiric therapy regimens. This chapter will explore the methods used for antimicrobial susceptibility testing of bacterial pathogens.

Keywords

Minimal Inhibitory Concentration Antimicrobial Agent Antimicrobial Susceptibility Disk Diffusion Bacterial Vaginosis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Humana Press, a part of Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Fred C. Tenover
    • 1
  1. 1.Scientific Affairs, CepheidSunnyvaleUSA

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