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How to measure the impacts of antibiotic resistance and antibiotic development on empiric therapy: new composite indices
  1. Josie S Hughes1,
  2. Amy Hurford2,
  3. Rita L Finley3,
  4. David M Patrick4,5,
  5. Jianhong Wu1,
  6. Andrew M Morris6,7
  1. 1Centre for Disease Modelling, York University, Toronto, Ontario, Canada
  2. 2Department of Biology and Department of Mathematics and Statistics, Memorial University of Newfoundland, St. John's, Newfoundland, Canada
  3. 3Centre for Food-borne, Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, Ontario, Canada
  4. 4Centre for Disease Control, Vancouver, British Columbia, Canada
  5. 5School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
  6. 6Department of Medicine, Mount Sinai Hospital and University Health Network, Toronto, Ontario, Canada
  7. 7Department of Medicine, University of Toronto, Toronto, Ontario, Canada
  1. Correspondence to Dr Andrew M Morris; andrew.morris{at}sinaihealthsystem.ca

Abstract

Objectives We aimed to construct widely useable summary measures of the net impact of antibiotic resistance on empiric therapy. Summary measures are needed to communicate the importance of resistance, plan and evaluate interventions, and direct policy and investment.

Design, setting and participants As an example, we retrospectively summarised the 2011 cumulative antibiogram from a Toronto academic intensive care unit.

Outcome measures We developed two complementary indices to summarise the clinical impact of antibiotic resistance and drug availability on empiric therapy. The Empiric Coverage Index (ECI) measures susceptibility of common bacterial infections to available empiric antibiotics as a percentage. The Empiric Options Index (EOI) varies from 0 to ‘the number of treatment options available’, and measures the empiric value of the current stock of antibiotics as a depletable resource. The indices account for drug availability and the relative clinical importance of pathogens. We demonstrate meaning and use by examining the potential impact of new drugs and threatening bacterial strains.

Conclusions In our intensive care unit coverage of device-associated infections measured by the ECI remains high (98%), but 37–44% of treatment potential measured by the EOI has been lost. Without reserved drugs, the ECI is 86–88%. New cephalosporin/β-lactamase inhibitor combinations could increase the EOI, but no single drug can compensate for losses. Increasing methicillin-resistant Staphylococcus aureus (MRSA) prevalence would have little overall impact (ECI=98%, EOI=4.8–5.2) because many Gram-positives are already resistant to β-lactams. Aminoglycoside resistance, however, could have substantial clinical impact because they are among the few drugs that provide coverage of Gram-negative infections (ECI=97%, EOI=3.8–4.5). Our proposed indices summarise the local impact of antibiotic resistance on empiric coverage (ECI) and available empiric treatment options (EOI) using readily available data. Policymakers and drug developers can use the indices to help evaluate and prioritise initiatives in the effort against antimicrobial resistance.

  • antimicrobial resistance
  • composite index
  • cumulative antibiogram
  • device-associated infection
  • burden of resistance

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

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Footnotes

  • Contributors AMM, JW and AH developed the research question. JSH led the development of the indices and the writing. All authors provided invaluable guidance and feedback throughout.

  • Funding This work was supported by the Canadian Institutes of Health Research and the Natural Sciences and Engineering Research Council of Canada (grant number 446610-3).

  • Competing interests We do not have commercial or other associations that might pose a conflict of interest.

  • Ethics approval Mount Sinai Hospital Research Ethics Board.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement Table 4 contains example antibiogram data.

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