Evidence map›Paper›PMID 37508273›Full record

ArticleAntibiotics (Basel, Switzerland)2023

A Scoping Review of Antimicrobial Usage and Antimicrobial Resistance in Beef Cow-Calf Herds in the United States and Canada.

Barbara Wilhelm, Jayce Fossen, Sheryl Gow, Cheryl Waldner

Open access · goldAbstract readScoping Review
In one paragraph

Article in Antibiotics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.5field-weighted citation impact, top 19% of its field
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

4 citing papers in PubMed, 8 citations in OpenAlex.

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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

4 authors at 2 institutions in 1 country.

Barbara WilhelmBig Sky Health Analytics, Vermilion, AB T9X 2B3, Canada.
Jayce FossenDepartment of Large Animal Clinical Sciences, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK S7N 5B4, Canada.ORCID 0000-0002-3461-8736
Sheryl GowPublic Health Agency of Canada, Saskatoon, SK S7N 5B4, Canada.
Cheryl WaldnerDepartment of Large Animal Clinical Sciences, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK S7N 5B4, Canada.ORCID 0000-0002-7152-4261
University of Saskatchewan · CAPublic Health Agency of Canada · CA

Funding

Natural Sciences and Engineering Research Council 548206 - 18
6 · The paper itself

Abstract

backgroundThe magnitude and knowledge gaps regarding antimicrobial use (AMU) and antimicrobial resistance (AMR) have not been summarized for the North American cow-calf production sector, although estimates of AMU and AMR are essential to AMR risk analysis. The objectives of this scoping review were to map AMU and AMR in the beef cow-calf sector in Canada and the United States, summarize published AMU/AMR predictors, and identify research gaps.

methodsAn electronic search was conducted of four bibliographic databases and Google Scholar, augmented by a hand-search of captured studies.

resultsTwenty-three of three-hundred and forty-three publications screened advanced to data extraction. Of these, 10 were conducted in the USA and 13 in Canada. Thirteen studied AMR and twelve studied AMU, with two reporting both. Of twelve captured AMU studies, nine presented counts of herd AMU by antimicrobial class or specific antimicrobial. Antimicrobial resistance in

conclusionsOverall, a small number of AMR studies were available for synthesis in primarily one population (cows) reporting

Indexed as

antibiotic resistanceantibiotic useantimicrobial susceptibilitybeef calfbeef cow

Identifiers

PMID37508273
PMCPMC10376086
OpenAlexW4384067910

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.