Evidence map›Paper›PMID 26338047›Full record

SynthesisThe Journal of antimicrobial chemotherapy2015

Impact of mupirocin resistance on the transmission and control of healthcare-associated MRSA.

Sarah R Deeny, Colin J Worby, Olga Tosas Auguet, Ben S Cooper, Jonathan Edgeworth, Barry Cookson, Julie V Robotham

Abstract readMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in The Journal of antimicrobial chemotherapy, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
–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

9 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Article
  5. Bayesian Calibration to Address the Challenge of Antimicrobial Resistance: A Review.IEEE access : practical innovations, open solutions · 2024
    Article
  6. Article
  7. Review
  8. Article
  9. 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

7 authors.

Sarah R DeenyModelling and Economics Unit, Centre for Infectious Disease Surveillance and Control, Public Health England and Health Protection Research Unit in Modelling Methodology, London, UK sarah.deeny@phe.gov.uk.
Colin J WorbyCenter for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA, USA.
Olga Tosas AuguetCentre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, King's College London, London, UK Guy's and St Thomas' NHS Foundation Trust, London, UK.
Ben S CooperCentre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK Mahidol-Oxford Tropical Medicine Research Unit, Bangkok, Thailand.
Jonathan EdgeworthCentre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, King's College London, London, UK Guy's and St Thomas' NHS Foundation Trust, London, UK.
Barry CooksonDivision of Infection and Immunity, University College London, London, UK.
Julie V RobothamModelling and Economics Unit, Centre for Infectious Disease Surveillance and Control, Public Health England and Health Protection Research Unit in Modelling Methodology, London, UK.

Funding

Understanding and controlling antibiotic resistanceU54GM088558 · NIGMS · HARVARD SCHOOL OF PUBLIC HEALTH · PI LIPSITCH, MARC · 2009 to 2018
$26.4M
Medical Research Council MR/K006924/1NIGMS NIH HHS U54 GM088558NIGMS NIH HHS U54GM088558Wellcome Trust 089275/Z/09/ZWellcome Trust 106491/Z/14/Z
6 · The paper itself

Abstract

objectivesThe objectives of this study were to estimate the relative transmissibility of mupirocin-resistant (MupR) and mupirocin-susceptible (MupS) MRSA strains and evaluate the long-term impact of MupR on MRSA control policies.

methodsParameters describing MupR and MupS strains were estimated using Markov chain Monte Carlo methods applied to data from two London teaching hospitals. These estimates parameterized a model used to evaluate the long-term impact of MupR on three mupirocin usage policies: 'clinical cases', 'screen and treat' and 'universal'. Strategies were assessed in terms of colonized and infected patient days and scenario and sensitivity analyses were performed.

resultsThe transmission probability of a MupS strain was 2.16 (95% CI 1.38-2.94) times that of a MupR strain in the absence of mupirocin usage. The total prevalence of MupR in colonized and infected MRSA patients after 5 years of simulation was 9.1% (95% CI 8.7%-9.6%) with the 'screen and treat' mupirocin policy, increasing to 21.3% (95% CI 20.9%-21.7%) with 'universal' mupirocin use. The prevalence of MupR increased in 50%-75% of simulations with 'universal' usage and >10% of simulations with 'screen and treat' usage in scenarios where MupS had a higher transmission probability than MupR.

conclusionsOur results provide evidence from a clinical setting of a fitness cost associated with MupR in MRSA strains. This provides a plausible explanation for the low levels of mupirocin resistance seen following 'screen and treat' mupirocin usage. From our simulations, even under conservative estimates of relative transmissibility, we see long-term increases in the prevalence of MupR given 'universal' use.

Indexed as

Drug Resistance, BacterialAnti-Infective Agents, LocalCarrier StateCross InfectionDisease Transmission, InfectiousHospitals, TeachingHumansInfection ControlLondonMethicillin-Resistant Staphylococcus aureusModels, StatisticalMupirocinOrganizational PolicyPrevalenceStaphylococcal InfectionsAnti-Infective Agents, LocalMupirocin

Identifiers

PMID26338047
PMCPMC4652683

What OpenQuestion holds

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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.