Cumulative Antimicrobial Susceptibility Data from Intensive Care Units at One Institution: Should Data Be Combined?

Aaron Campigotto1, Matthew P Muller2, Linda R Taggart2

  • 1Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada.

Insights

Pooling intensive care unit (ICU) susceptibility data may mask important resistance trends. A rolling-average method for cumulative antimicrobial susceptibility test data (CSTD) better reflects unit-specific resistance patterns, improving empirical therapy guidance.

Area of Science:

  • Clinical Microbiology
  • Infectious Diseases
  • Hospital Epidemiology

Background:

  • Cumulative antimicrobial susceptibility test data (CSTD) are crucial for guiding empirical therapy and monitoring antibiotic resistance trends.
  • Current guidelines recommend annual CSTD reporting, often leading hospitals to aggregate data from multiple intensive care units (ICUs).
  • Aggregating data across diverse ICU patient populations may obscure significant variations in antimicrobial resistance.

Purpose of the Study:

  • To evaluate the appropriateness of combining CSTD from different ICUs for empirical therapy guidance.
  • To compare a traditional CSTD reporting method with a novel rolling-average CSTD method.
  • To assess the impact of different CSTD aggregation strategies on identifying antimicrobial resistance variations.

Main Methods:

  • Susceptibility data for common Gram-negative organisms (Escherichia coli, Pseudomonas aeruginosa) and key antibiotics were analyzed.
  • Two methods were employed: a traditional CSTD combining data from two ICUs and a rolling-average CSTD pooling 2 years of data per ICU.
  • Organism-antimicrobial combinations were examined to identify differences in susceptibility between ICUs and over time.

Main Results:

  • The rolling-average method revealed significant between-ICU susceptibility differences in 50% of organism-antimicrobial combinations.
  • Median year-over-year susceptibility differences were 3% with the traditional method versus 14% for between-ICU comparisons using the rolling-average method.
  • The revised approach led to changes in empirical antibiotic selection, highlighting the limitations of pooled ICU data.

Conclusions:

  • Pooling CSTD from ICUs with distinct patient populations may not accurately guide empirical antimicrobial therapy.
  • A rolling-average CSTD method offers a more granular approach, providing unit-specific resistance data.
  • Implementing a rolling-average strategy can enhance the accuracy of CSTD for individual ICUs and improve antimicrobial stewardship.

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