Evidence map›Paper›PMID 36851371›Full record

ArticleVeterinary sciences2023

Comprehensive Outcomes Affected by Antimicrobial Metaphylaxis of Feedlot Calves at Medium-Risk for Bovine Respiratory Disease from a Randomized Controlled Trial.

Lucas M Horton, Brandon E Depenbusch, Diana M Dewsbury, Taylor B McAtee, Nick B Betts, David G Renter

Abstract read
In one paragraph

Article in Veterinary sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

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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

6 authors.

Lucas M HortonThe Center for Outcomes Research and Epidemiology, Department of Diagnostic Medicine and Pathobiology, Kansas State University College of Veterinary Medicine, Manhattan, KS 66506, USA.
Brandon E DepenbuschInnovative Livestock Services, Inc., Great Bend, KS 67530, USA.
Diana M DewsburyThe Center for Outcomes Research and Epidemiology, Department of Diagnostic Medicine and Pathobiology, Kansas State University College of Veterinary Medicine, Manhattan, KS 66506, USA.
Taylor B McAteeThe Center for Outcomes Research and Epidemiology, Department of Diagnostic Medicine and Pathobiology, Kansas State University College of Veterinary Medicine, Manhattan, KS 66506, USA.ORCID 0000-0002-9352-3657
Nick B BettsElanco Animal Health, Greenfield, IN 46140, USA.
David G RenterThe Center for Outcomes Research and Epidemiology, Department of Diagnostic Medicine and Pathobiology, Kansas State University College of Veterinary Medicine, Manhattan, KS 66506, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The objectives were to evaluate the effects of metaphylaxis (META) and pull-and-treat (PT) programs on health, antimicrobial use, beef production, economics, and greenhouse gas emissions in cattle at medium risk for bovine respiratory disease (BRD). A randomized complete block design was used at two US commercial feedlots. Steers and heifers [2366 total; 261 (±11.0) kg initial weight] were blocked by sex and feedlot arrival, and allocated to one of two pens within a block (16 pens total, eight blocks). Pens were randomly assigned to treatment: META, tulathromycin injection at initial processing; or PT, tulathromycin injection only for first clinical BRD treatment. Data were analyzed with linear and generalized linear mixed models. There was greater BRD morbidity in PT than META cattle (17.2% vs. 7.3% respectively;

Indexed as

antimicrobial usebeef cattlebovine respiratory diseaseeconomicsfeedlotmedium-riskmetaphylaxissustainabilitywelfare

Identifiers

PMID36851371
PMCPMC9960805

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.