Influence of analysis conditions for antimicrobial susceptibility test data on susceptibility rates

PLoS One. 2020 Jun 23;15(6):e0235059. doi: 10.1371/journal.pone.0235059. eCollection 2020.

Abstract

Background: To support effective antibiotic selection in empirical treatments, infection control interventions, and antimicrobial resistance containment strategies, many medical institutions collect antimicrobial susceptibility test data conducted at their facilities to prepare cumulative antibiograms.

Aim: To evaluate how the setpoints of duplicate isolate removal period and data collection period affect the calculated susceptibility rates in antibiograms.

Methods: The Sakai City Medical Center is a regional core hospital for tertiary emergency medical care with 480 beds for general clinical care. In this study, all the Pseudomonas aeruginosa, Escherichia coli, and Klebsiella pneumoniae isolates collected at the Sakai City Medical Center Clinical Laboratory between July 2013 and December 2018 were subjected to antimicrobial susceptibility tests and the resulting data was analyzed.

Findings: The longer the duplicate isolate removal period, the fewer the isolates are available for every bacterial species. Differences in the length of the duplicate isolate removal period affected P. aeruginosa susceptibility rates to β-lactam antibiotics by up to 10.8%. The setpoint of the data collection period affected the antimicrobial susceptibility rates by up to 7.3%. We found that a significant change in susceptibility could be missed depending on the setting of the data collection period, in preparing antibiogram of β-lactam antibiotics for P. aeruginosa.

Conclusions: When referring to antibiograms, medical professionals involved in infectious disease treatment should be aware that the parameter values, such as the duplicate isolate removal period and the data collection period, affect P. aeruginosa susceptibility rates especially to β-lactam antibiotics. And antibiogram should be updated within the shortest time period that is practically possible, taking into account restrictions such as numbers of specimen.

MeSH terms

  • Algorithms
  • Anti-Bacterial Agents / pharmacology*
  • Emergency Service, Hospital
  • Escherichia coli / drug effects*
  • Escherichia coli / isolation & purification
  • Escherichia coli / physiology
  • Hospitalization / statistics & numerical data
  • Humans
  • Klebsiella pneumoniae / drug effects*
  • Klebsiella pneumoniae / isolation & purification
  • Klebsiella pneumoniae / physiology
  • Microbial Sensitivity Tests / methods*
  • Microbial Sensitivity Tests / standards*
  • Pseudomonas aeruginosa / drug effects*
  • Pseudomonas aeruginosa / isolation & purification
  • Pseudomonas aeruginosa / physiology
  • Tertiary Care Centers
  • Time Factors

Substances

  • Anti-Bacterial Agents

Grants and funding

The authors received no specific funding for this work.