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Related Experiment Videos

Resistance-pattern-analysis--a step toward predictable differentiated antibiotic therapy.

W Fegeler1, D Lintz, W Ritzerfeld

  • 1Institute of Medical Microbiology, Westphalien Wilhelms-University Münster.

Zentralblatt Fur Bakteriologie, Mikrobiologie, Und Hygiene. Series A, Medical Microbiology, Infectious Diseases, Virology, Parasitology
|November 1, 1988
PubMed
Summary

Resistance-Pattern-Analysis (RPA) allows antibiotic susceptibility comparisons, independent of patient factors. Aztreonam demonstrated superior efficacy against tested bacterial isolates compared to amikacin and gentamicin.

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Area of Science:

  • Microbiology
  • Infectious Diseases
  • Pharmacology

Background:

  • Antibiotic susceptibility testing is crucial for effective treatment.
  • Patient and test-specific factors can complicate the interpretation of susceptibility results.
  • A standardized method is needed for objective antibiotic comparison.

Purpose of the Study:

  • To introduce and describe the Resistance-Pattern-Analysis (RPA) method.
  • To illustrate the RPA's utility in comparing antibiotic efficacy.
  • To demonstrate RPA's application in selecting empirical antibiotic therapy and cost-risk analysis.

Main Methods:

  • Resistance-Pattern-Analysis (RPA) was developed for objective comparison of antibiotic susceptibility data.
  • RPA was applied to analyze susceptibility results for 1526 bacterial isolates.

Related Experiment Videos

  • Antibiotics analyzed included aztreonam, gentamicin, and amikacin.
  • Main Results:

    • Aztreonam exhibited superior activity against all tested bacterial species compared to amikacin.
    • Aztreonam demonstrated the best results against Pseudomonadaceae when compared to gentamicin.
    • The study illustrated RPA's potential for comparative assessment and therapy selection.

    Conclusions:

    • Resistance-Pattern-Analysis (RPA) provides a robust method for comparing antibiotic effectiveness.
    • RPA facilitates informed antibiotic selection for both established and empirical therapies.
    • The method supports cost-risk analysis in medical microbiology and infectious disease management.