Evidence map›Paper›PMID 32704830›Full record

ArticleTranslational animal science2019

Prevalence and lameness-associated risk factors in Alberta feedlot cattle.

Jessica Davis-Unger, Karen S G Schwartzkopf-Genswein, Ed A Pajor, Steve Hendrick, Sonia Marti, Craig Dorin, Karin Orsel

Open access · goldAbstract read
In one paragraph

Article in Translational animal science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
2.2field-weighted citation impact, top 14% 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

22 citing papers in PubMed, 43 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Welfare of beef cattle.EFSA journal. European Food Safety Authority · 2025
    Article
  6. Health outcomes following antimicrobial treatment of septic arthritis in Canadian feedlot calves.The Canadian veterinary journal = La revue veterinaire canadienne · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Epidemiology of Digital Dermatitis in Western Canadian Feedlot Cattle.Animals : an open access journal from MDPI · 2024
    Article
  13. Review
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
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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

7 authors at 3 institutions in 2 countries.

Jessica Davis-UngerUniversity of Calgary, Faculty of Veterinary Medicine, Department of Production Animal Health, Calgary, Alberta, Canada.
Karen S G Schwartzkopf-GensweinAgriculture and Agri-Food Canada, Lethbridge Research and Development Center, Lethbridge, Alberta, Canada.
Ed A PajorUniversity of Calgary, Faculty of Veterinary Medicine, Department of Production Animal Health, Calgary, Alberta, Canada.
Steve HendrickCoaldale Veterinary Clinic, Coaldale, Alberta, Canada.
Sonia MartiUniversity of Calgary, Faculty of Veterinary Medicine, Department of Production Animal Health, Calgary, Alberta, Canada.
Craig DorinVeterinary Agri-Health Services, Airdrie, Alberta, Canada.
Karin OrselUniversity of Calgary, Faculty of Veterinary Medicine, Department of Production Animal Health, Calgary, Alberta, Canada.
University of Calgary · CAInstitute for Research and Technology in Food and Agriculture · ESLethbridge Research and Development Centre

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lameness in cattle is a health and welfare concern; however, limited information is available on risk factors and the relationship between lameness and common diseases like bovine respiratory disease (BRD). Therefore, the objectives of this study were to: 1) identify prevalence of lameness in feedlot cattle and related risk factors of cattle diagnosed as lame; and 2) determine associations between BRD occurrence and lameness. Feedlot cattle health records were available from 28 feedlots for 10 yr. The data set consisted of 663,838 cattle records, with 13.9% (92,156) diagnosed with a disease, including 32.3%, 46.0%, and 22.0% with lameness, BRD, and other diagnoses, respectively. Lameness was classified into four categories: foot rot (FR), joint infections (JI), lame with no visible swelling (LNVS), and injuries (INJ), with a prevalence of 74.5%, 16.1%, 6.1%, and 3.1%, respectively. Lameness was compared across cattle types (arrival date and weight) as well as age classification (calf vs. yearling), gender (steer vs. heifer), and season of placement in the feedlot (spring, summer, fall, and winter). Within the disease-diagnosed population, lameness represented 28.5% of treated fall-placed calves, 38.5% of winter-placed calves, and 40.8% of treated yearlings. Foot rot was the most common diagnosis with 74.5% of all lameness diagnoses, with winter- and fall-placed calves more likely to be diagnosed with FR compared to yearlings (OR: 1.19, 95% CI: 1.10-1.30 and OR: 1.46, 95% CI: 1.38-1.55, respectively). Joint infections were the second most common diagnosis (16.1%). Compared to yearlings, fall-placed calves had a higher odds (OR: 3.64, 95% CI: 3.12-4.24) for JI. Injuries and LNVS were the least common but again fall-placed calves had higher odds of this diagnosis compared to yearlings (OR: 2.26, 95% CI: 1.70-2.99 and OR: 9.10, 95% CI: 6.26-13.2, respectively). Gender was significantly different for JI as steers were less likely affected compared to heifers (OR: 0.687, 95% CI: 0.545-0.867), and more likely affected by LNVS (OR: 2.46, 95% CI: 1.57-3.84). Of all lameness-associated deaths, JI accounted for almost 50%. Finally, cattle diagnosed with BRD were subsequently more likely to be diagnosed with INJ, JI, or LNVS (

Indexed as

beef cattlefoot rotlameness diagnosisoccurrence

Identifiers

PMID32704830
PMCPMC7200549
OpenAlexW2921315578

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.