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Journal of Medical Microbiology logo Journal of Medical Microbiology

Volume 72, Issue 7

Quantifying patient- and hospital-level antimicrobial resistance dynamics in from routinely collected data Open Access

Abstract

Antimicrobial resistance (AMR) to all antibiotic classes has been found in the pathogen . The reported prevalence of these resistances varies, driven by within-host AMR evolution at the patient level, and between-host transmission at the hospital level. Without dense longitudinal sampling, pragmatic analysis of AMR dynamics at multiple levels using routine surveillance data is essential to inform control measures.

The value and limitations of routinely collected hospital data to gain insight into AMR dynamics at the hospital and individual levels simultaneously are unclear.

We explored AMR diversity in 70 000 isolates from a UK paediatric hospital between 2000–2021, using electronic datasets containing multiple routinely collected isolates per patient with phenotypic antibiograms and information on hospitalization and antibiotic consumption.

At the hospital level, the proportion of isolates that were meticillin-resistant (MRSA) increased between 2014–2020 from 25–50 %, before sharply decreasing to 30%, likely due to a change in inpatient demographics. Temporal trends in the proportion of isolates resistant to different antibiotics were often correlated in MRSA, but independent in meticillin-susceptible . Ciprofloxacin resistance in MRSA decreased from 70–40 % of tested isolates between 2007–2020, likely linked to a national policy to reduce fluoroquinolone usage in 2007. At the patient level, we identified frequent AMR diversity, with 4 % of patients ever positive for simultaneously carrying, at some point, multiple isolates with different resistances. We detected changes over time in AMR diversity in 3 % of patients ever positive for . These changes equally represented gain and loss of resistance.

Within this routinely collected dataset, we found that 65 % of changes in resistance within a patient’s population could not be explained by antibiotic exposure or between-patient transmission of bacteria, suggesting that within-host evolution via frequent gain and loss of AMR genes may be responsible for these changing AMR profiles. Our study highlights the value of exploring existing routine surveillance data to determine underlying mechanisms of AMR. These insights may substantially improve our understanding of the importance of antibiotic exposure variation, and the success of single clones.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): diversity , hospital data , resistance dynamics and S. aureus
Funding
This study was supported by the:
  • Medical Research Council (Award MR/P014658/1)
    • Principle Award Recipient: GwenanM Knight
  • National Institute of Allergy and Infectious Diseases, National Institutes of Health (Award 1R01AI146338)
    • Principle Award Recipient: LouisGrandjean
  • Wellcome Trust (Award 226007/Z/22/Z)
    • Principle Award Recipient: LouisGrandjean
  • Medical Research Council (Award MR/N013638/1)
    • Principle Award Recipient: AlastairClements
  • Medical Research Council (Award MR/N013638/1)
    • Principle Award Recipient: QuentinLeclerc
© 2023 The Authors
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License. This article was made open access via a Publish and Read agreement between the Microbiology Society and the corresponding author’s institution.
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2023-07-11
2025-04-29
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Quantifying patient- and hospital-level antimicrobial resistance dynamics in Staphylococcus aureus from routinely collected data
J. Med. Microbiol. 72, 001724 (2023); https://doi.org/10.1099/jmm.0.001724
/content/journal/jmm/10.1099/jmm.0.001724
/content/journal/jmm/10.1099/jmm.0.001724
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