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Related Concept Videos

Antimicrobial Effectiveness01:28

Antimicrobial Effectiveness

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The effectiveness of antimicrobial agents depends on various factors influencing their ability to eliminate microbial populations. Larger microbial populations require more time for complete eradication, emphasizing the importance of population size analysis when evaluating antimicrobial efficacy.Microbial resistance to antimicrobial agents varies significantly. Highly resilient microorganisms include endospores, gram-negative bacteria, and non-enveloped viruses, while prions are exceptionally...
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Development of Antibiotic Resistance01:30

Development of Antibiotic Resistance

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Antibiotic resistance is a major public health concern that arises when bacteria evolve mechanisms to withstand the effects of antibiotic treatments. This resistance can be intrinsic, acquired through genetic mutations, or transferred between bacteria via horizontal gene transfer. The development of antibiotic resistance poses significant challenges in treating bacterial infections and necessitates ongoing research to develop new therapeutic strategies.Intrinsic resistance occurs when bacterial...
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Antibiotic Selection00:57

Antibiotic Selection

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Updated: Aug 13, 2025

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Better antimicrobial resistance data analysis and reporting in less time.

Christian F Luz1, Matthijs S Berends1,2, Xuewei Zhou1

  • 1Department of Medical Microbiology and Infection Prevention, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ, Groningen, Netherlands.

Jac-Antimicrobial Resistance
|January 23, 2023
PubMed
Summary

A new open-source software significantly improves antimicrobial resistance (AMR) data analysis and reporting efficiency and accuracy. This tool enhances clinical decision-making by providing rapid, reliable insights into local microbial epidemiology and AMR levels.

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Area of Science:

  • Clinical Microbiology
  • Infectious Diseases
  • Health Informatics

Background:

  • Accurate local antimicrobial resistance (AMR) data is crucial for effective antimicrobial stewardship.
  • Existing tools for AMR data analysis and reporting often lack reliability and reproducibility.
  • This gap hinders informed decision-making in clinical antimicrobial use.

Purpose of the Study:

  • To compare traditional AMR data analysis methods with a novel software approach.
  • To evaluate the efficiency, accuracy, and usability of the new AMR data analysis tool in a clinical setting.

Main Methods:

  • Ten professionals analyzed blood culture and antimicrobial susceptibility data in two rounds: using their existing software and a new tool.
  • Data analysis accuracy and time spent were recorded and compared between the two rounds.
  • The usability of the new software was assessed using the System Usability Scale (SUS).

Main Results:

  • Mean reporting time decreased from 93.7 to 22.4 minutes (P < 0.001).
  • Task completion improved from 56% to 96% (P < 0.05), and accuracy increased from 37.9% to 97.9% (P < 0.001).
  • The new tool achieved a median usability score of 83.8 out of 100.

Conclusions:

  • Open-source software significantly enhances the efficiency and accuracy of AMR data analysis and reporting workflows.
  • Integration of these tools into clinical settings can provide timely and dependable insights into local microbial epidemiology and AMR.
  • This approach supports evidence-based antimicrobial use and improves patient care.