Evidence map›Paper›PMID 32280945›Full record

ArticleJAC-antimicrobial resistance2019

Case-based surveillance of antimicrobial resistance with full susceptibility profiles.

Sukhyun Ryu, Benjamin J Cowling, Peng Wu, Scott Olesen, Christophe Fraser, Daphne S Sun, Marc Lipsitch, Yonatan H Grad

Abstract read
In one paragraph

Article in JAC-antimicrobial resistance, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Surveillance strategies using routine microbiology for antimicrobial resistance in low- and middle-income countries.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2021
    Review
  13. Article
  14. Observational
  15. Article
  16. Article
  17. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Sukhyun RyuWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.ORCID 0000-0002-8915-8167
Benjamin J CowlingWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
Peng WuWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
Scott OlesenDepartment of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA.ORCID 0000-0001-5400-4945
Christophe FraserBig Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
Daphne S SunDepartment of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Marc LipsitchDepartment of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA.ORCID 0000-0003-1504-9213
Yonatan H GradDepartment of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Funding

Understanding and controlling antibiotic resistanceU54GM088558 · NIGMS · HARVARD SCHOOL OF PUBLIC HEALTH · PI HANAGE, WILLIAM · 2009 to 2018
$26.4M
NIGMS NIH HHS U54 GM088558
6 · The paper itself

Abstract

Surveillance of antimicrobial resistance (AMR) is essential for clinical decision-making and for public health authorities to monitor patterns in resistance and evaluate the effectiveness of interventions and control measures. Existing AMR surveillance is typically based on reports from hospital laboratories and public health laboratories, comprising reports of pathogen frequencies and resistance frequencies among each species detected. Here we propose an improved framework for AMR surveillance, in which the unit of surveillance is patients with specific conditions, rather than biological samples of a particular type. In this 'case-based' surveillance, denominators as well as numerators will be clearly defined with clinical relevance and more comparable at the local, national and international level. In locations with sufficient resources, individual-based data on patient characteristics and full antibiotic susceptibility profiles would provide high-quality evidence for monitoring resistant pathogens of clinical importance, clinical treatment of infections and public health responses to outbreaks of infections with resistant bacteria.

Identifiers

PMID32280945
PMCPMC7134534

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.