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How to measure the impacts of antibiotic resistance and antibiotic development on empiric therapy: new composite indices
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 PARTICIPANT...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5168677/ https://www.ncbi.nlm.nih.gov/pubmed/27986734 http://dx.doi.org/10.1136/bmjopen-2016-012040 |
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author | Hughes, Josie S Hurford, Amy Finley, Rita L Patrick, David M Wu, Jianhong Morris, Andrew M |
author_facet | Hughes, Josie S Hurford, Amy Finley, Rita L Patrick, David M Wu, Jianhong Morris, Andrew M |
author_sort | Hughes, Josie S |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5168677 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-51686772016-12-22 How to measure the impacts of antibiotic resistance and antibiotic development on empiric therapy: new composite indices Hughes, Josie S Hurford, Amy Finley, Rita L Patrick, David M Wu, Jianhong Morris, Andrew M BMJ Open Infectious Diseases 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. BMJ Publishing Group 2016-12-16 /pmc/articles/PMC5168677/ /pubmed/27986734 http://dx.doi.org/10.1136/bmjopen-2016-012040 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/ 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/ |
spellingShingle | Infectious Diseases Hughes, Josie S Hurford, Amy Finley, Rita L Patrick, David M Wu, Jianhong Morris, Andrew M How to measure the impacts of antibiotic resistance and antibiotic development on empiric therapy: new composite indices |
title | How to measure the impacts of antibiotic resistance and antibiotic development on empiric therapy: new composite indices |
title_full | How to measure the impacts of antibiotic resistance and antibiotic development on empiric therapy: new composite indices |
title_fullStr | How to measure the impacts of antibiotic resistance and antibiotic development on empiric therapy: new composite indices |
title_full_unstemmed | How to measure the impacts of antibiotic resistance and antibiotic development on empiric therapy: new composite indices |
title_short | How to measure the impacts of antibiotic resistance and antibiotic development on empiric therapy: new composite indices |
title_sort | how to measure the impacts of antibiotic resistance and antibiotic development on empiric therapy: new composite indices |
topic | Infectious Diseases |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5168677/ https://www.ncbi.nlm.nih.gov/pubmed/27986734 http://dx.doi.org/10.1136/bmjopen-2016-012040 |
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