- Abstract:
-
BACKGROUND: There is a pressing need to understand better the extent and distribution of antimicrobial resistance on a global scale, to inform development of effective interventions. Collation of datasets for meta-analysis, mathematical modelling and temporo-spatial analysis is hampered by the considerable variability in clinical sampling, variable quality in laboratory practice and inconsistencies in antimicrobial susceptibility testing and reporting.
METHO...
Expand abstract - Publication status:
- Published
- Peer review status:
- Peer reviewed
- Version:
- Publisher's Version
- Files:
-
-
(pdf, 968.8KB)
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- Publisher copy:
- 10.1186/s12916-019-1301-1
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- Publisher:
- BMC Publisher's website
- Journal:
- BMC Medicine Journal website
- Volume:
- 17
- Issue:
- 1
- Pages:
- 70
- Publication date:
- 2019-03-29
- Acceptance date:
- 2019-03-06
- DOI:
- EISSN:
-
1741-7015
- Pubs id:
-
pubs:987006
- URN:
-
uri:0e3b82d0-1968-4163-b655-ad5c1129e383
- UUID:
-
uuid:0e3b82d0-1968-4163-b655-ad5c1129e383
- Local pid:
- pubs:987006
- Language:
- English
- Keywords:
- Copyright holder:
- Turner et al.
- Copyright date:
- 2019
- Notes:
- © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Journal article
Microbiology Investigation Criteria for Reporting Objectively (MICRO): a framework for the reporting and interpretation of clinical microbiology data
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