Evidence map›Paper›PMID 28270258›Full record

ArticleInfection control and hospital epidemiology2017

The Impact of Reducing Antibiotics on the Transmission of Multidrug-Resistant Organisms.

Sean L Barnes, Clare Rock, Anthony D Harris, Sara E Cosgrove, Daniel J Morgan, Kerri A Thom

Abstract read
In one paragraph

Article in Infection control and hospital epidemiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Trial
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Observational
  13. Article
  14. Carbapenem-resistantFrontiers in microbiology · 2022
    Review
  15. Article
  16. Antibiotic modification versus withhold in febrile patients without evidence of bacterial infection, unresponsive to initial empiric regimen: a multicentre retrospective study conducted in Israel.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2020
    Article
  17. Article
  18. The Infinity War: How to Cope with Carbapenem-resistantJournal of Korean medical science · 2018
    Review
  19. Article
  20. Review
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

6 authors.

Sean L Barnes1Robert H. Smith School of Business,University of Maryland,College Park,Maryland.
Clare Rock2Department of Medicine,Division of Infectious Diseases,The Johns Hopkins University School of Medicine,Baltimore,Maryland.
Anthony D Harris3Department of Epidemiology and Public Health,University of Maryland School of Medicine,Baltimore,Maryland.
Sara E Cosgrove2Department of Medicine,Division of Infectious Diseases,The Johns Hopkins University School of Medicine,Baltimore,Maryland.
Daniel J Morgan3Department of Epidemiology and Public Health,University of Maryland School of Medicine,Baltimore,Maryland.
Kerri A Thom3Department of Epidemiology and Public Health,University of Maryland School of Medicine,Baltimore,Maryland.

Funding

K24 Clinical Research in Antimicrobial Resistance and Hospital EpidemiologyK24AI079040 · NIAID · UNIVERSITY OF MARYLAND BALTIMORE · PI HARRIS, ANTHONY D · 2009 to 2018
$1.8M
Epidemiology of Acinetobacter baumannii: An Emerging Nosocomial PathogenK23AI082450 · NIAID · UNIVERSITY OF MARYLAND BALTIMORE · PI THOM, KERRI · 2010 to 2014
$674k
NIAID NIH HHS K23 AI082450NIAID NIH HHS K24 AI079040
6 · The paper itself

Abstract

OBJECTIVE Antibiotic resistance is a major threat to public health. Resistance is largely driven by antibiotic usage, which in many cases is unnecessary and can be improved. The impact of decreasing overall antibiotic usage on resistance is unknown and difficult to assess using standard study designs. The objective of this study was to explore the potential impact of reducing antibiotic usage on the transmission of multidrug-resistant organisms (MDROs). DESIGN We used agent-based modeling to simulate interactions between patients and healthcare workers (HCWs) using model inputs informed by the literature. We modeled the effect of antibiotic usage as (1) a microbiome effect, for which antibiotic usage decreases competing bacteria and increases the MDRO transmission probability between patients and HCWs and (2) a mutation effect that designates a proportion of patients who receive antibiotics to subsequently develop a MDRO via genetic mutation. SETTING Intensive care unit INTERVENTIONS Absolute reduction in overall antibiotic usage by experimental values of 10% and 25% RESULTS Reducing antibiotic usage absolutely by 10% (from 75% to 65%) and 25% (from 75% to 50%) reduced acquisition rates of high-prevalence MDROs by 11.2% (P<.001) and 28.3% (P<.001), respectively. We observed similar effect sizes for low-prevalence MDROs. CONCLUSIONS In a critical care setting, where up to 50% of antibiotic courses may be inappropriate, even a moderate reduction in antibiotic usage can reduce MDRO transmission. Infect Control Hosp Epidemiol 2017;38:663-669.

Indexed as

Antimicrobial StewardshipDrug Resistance, Multiple, BacterialModels, BiologicalAcinetobacter baumanniiAnti-Bacterial AgentsBacterial InfectionsCarbapenem-Resistant EnterobacteriaceaeComputer SimulationCross InfectionHumansIntensive Care UnitsMethicillin-Resistant Staphylococcus aureusMicrobiotaPseudomonas aeruginosaVancomycin-Resistant EnterococciAnti-Bacterial Agents

Identifiers

PMID28270258
PMCPMC6416785

What OpenQuestion holds

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Registered trials

None linked

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.