Evidence map›Paper›PMID 39996263›Full record

ArticleFrontiers in veterinary science2024

Staphylococcal skin infection isolates from dogs without recent antibiotic exposure are 100% susceptible to clindamycin.

W Cooper Brookshire, Larry D Ballard, Vernon C Langston, Joo Youn Park, Keun-Seok Seo

Erratum issuedAbstract read
In one paragraph

Article in Frontiers in veterinary science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

W Cooper BrookshireDepartment of Clinical Sciences, College of Veterinary Medicine, Mississippi State University, Mississippi State, MS, United States.
Larry D BallardDepartment of Pathobiology and Population Medicine, College of Veterinary Medicine, Mississippi State University, Mississippi State, MS, United States.
Vernon C LangstonDepartment of Clinical Sciences, College of Veterinary Medicine, Mississippi State University, Mississippi State, MS, United States.
Joo Youn ParkDepartment of Comparative Biomedical Sciences, College of Veterinary Medicine, Mississippi State University, Mississippi State, MS, United States.
Keun-Seok SeoDepartment of Comparative Biomedical Sciences, College of Veterinary Medicine, Mississippi State University, Mississippi State, MS, United States.

Funding

Tracking and Evaluation CoreU54GM115428 · NIGMS · UNIVERSITY OF MISSISSIPPI MED CTR · PI COMPRETTA, CAROLINE E. · 2016 to 2025
$38.2M
NIGMS NIH HHS U54 GM115428
6 · The paper itself

Abstract

The objective of this study was to create an antibiogram representative of bacterial skin infections in canine patients that would typically be treated empirically, i.e., without risk factors for antibiotic resistance, such as a history of recent antibiotic use, antibiotic treatment failure, or recurrent infections. Traditional antibiograms are a form of passive surveillance and report antibiotic susceptibility of isolates from a specific laboratory, hospital, or region for a given period of time. However, traditional antibiograms are biased towards more resistance, because infections that have antibiotic susceptibility tests are more likely to be resistant, due to risk factors such as recent antibiotic treatment, hospitalization, or a history of previous antibiotic-resistant infections. Antibiotic susceptibility testing was performed on 67 pathogenic canine staphylococcal isolates (62

Indexed as

antibiogrambacterial folliculitiscaninepyodermaS. schleiferi antibiotic resistanceStaphylococcus pseudintermediusveterinary

Identifiers

PMID39996263
PMCPMC11847803

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.