Evidence map›Paper›PMID 29402294›Full record

ArticleBMC veterinary research2018

An epidemiologic study of antimicrobial resistance of Staphylococcus species isolated from equine samples submitted to a diagnostic laboratory.

Ronita Adams, Jackie Smith, Stephen Locke, Erica Phillips, Erdal Erol, Craig Carter, Agricola Odoi

Abstract read
In one paragraph

Article in BMC veterinary research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Prevalence ofSouthern African journal of infectious diseases · 2023
    Article
  6. Article
  7. Article
  8. A retrospective study on methicillin-resistantThe Canadian veterinary journal = La revue veterinaire canadienne · 2020
    Article
  9. Review
  10. Article
  11. 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.

Ronita AdamsDepartment of Biomedical and Diagnostic Sciences, University of Tennessee, College of Veterinary Medicine, 2407 River Dr., Knoxville, TN, 37996, USA.
Jackie SmithUniversity of Kentucky, Veterinary Diagnostic Laboratory, 1490 Bull Lea Rd., Lexington, KY, 40511, USA.
Stephen LockeUniversity of Kentucky, Veterinary Diagnostic Laboratory, 1490 Bull Lea Rd., Lexington, KY, 40511, USA.
Erica PhillipsUniversity of Kentucky, Veterinary Diagnostic Laboratory, 1490 Bull Lea Rd., Lexington, KY, 40511, USA.
Erdal ErolUniversity of Kentucky, Veterinary Diagnostic Laboratory, 1490 Bull Lea Rd., Lexington, KY, 40511, USA.
Craig CarterUniversity of Kentucky, Veterinary Diagnostic Laboratory, 1490 Bull Lea Rd., Lexington, KY, 40511, USA.
Agricola OdoiDepartment of Biomedical and Diagnostic Sciences, University of Tennessee, College of Veterinary Medicine, 2407 River Dr., Knoxville, TN, 37996, USA. aodoi@utk.edu.ORCID http://orcid.org/0000-0001-5050-6737

Funding

University of Tennessee Center of Excellence in Livestock Diseases and Human Health (COE) Research Award N/A
6 · The paper itself

Abstract

backgroundAntimicrobial resistance limits traditional treatment options and increases costs. It is therefore important to estimate the magnitude of the problem so as to provide empirical data to guide control efforts. The aim of this study was to investigate the burden and patterns of antimicrobial resistance (AMR) among equine Staphylococcus samples submitted to the University of Kentucky Veterinary Diagnostic Laboratory (UKVDL) from 1993 to 2009. Retrospective data of 1711 equine Staphylococcus samples submitted to the UKVDL during the time period 1993 to 2009 were included in the study. Antimicrobial susceptibility testing, that included 16 drugs, were performed using cultures followed by the Kirby-Bauer disk diffusion susceptibility test. The proportion of resistant isolates by animal breed, species of organism, sample source, and time period were computed. Chi-square and Cochran-Armitage trend tests were used to identify significant associations and temporal trends, respectively. Logistic regression models were used to investigate predictors of AMR and multidrug resistance (MDR).

resultsA total of 66.3% of the isolates were resistant to at least one antimicrobial, most of which were Staphylococcus aureus (77.1%), while 25.0% were MDR. The highest level of resistance was to penicillins (52.9%). Among drug classes, isolates had the highest rate of AMR to at least one type of β-lactams (49.2%), followed by aminoglycosides (30.2%). Significant (p < 0.05) associations were observed between odds of AMR and horse breed, species of organism and year. Similarly, significant (p < 0.05) associations were identified between odds of MDR and breed and age. While some isolates had resistance to up to 12 antimicrobials, AMR profiles featuring single antimicrobials such as penicillin were more common than those with multiple antimicrobials.

conclusionDemographic factors were significant predictors of AMR and MDR. The fact that some isolates had resistance to up to 12 of the 16 antimicrobials assessed is quite concerning. To address the high levels of AMR and MDR observed in this study, future studies will need to focus on antimicrobial prescription practices and education of both practitioners and animal owners on judicious use of antimicrobials to slow down the development of resistance.

Indexed as

Drug Resistance, BacterialAge FactorsAnimalsAnti-Bacterial AgentsDrug Resistance, Multiple, BacterialFemaleHorse DiseasesHorsesKentuckyMaleMicrobial Sensitivity TestsRetrospective StudiesStaphylococcal InfectionsStaphylococcusAnti-Bacterial AgentsAntimicrobial resistanceBurdenEquineHorsesKentuckyLogistic regression modelMultidrug resistancePredictorsStaphylococcus

Identifiers

PMID29402294
PMCPMC5800099

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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.