Predicting bovine respiratory disease outcome in feedlot cattle using latent class analysis
Open accessAbstract
Bovine respiratory disease (BRD) is the most significant disease affecting feedlot cattle. Indicators of BRD often used in feedlots such as visual signs, rectal temperature, computer-assisted lung auscultation (CALA) score, the number of BRD treatments, presence of viral pathogens, viral seroconversion, and lung damage at slaughter vary in their ability to predict an animal’s BRD outcome, and no studies have been published determining how a combination of these BRD indicators may define the number of BRD disease outcome groups. The objectives of the current study were (1) to identify BRD outcome groups using BRD indicators collected during the feeding phase and at slaughter through latent class analysis (LCA) and (2) to determine the importance of these BRD indicators to predict disease outcome. Animals with BRD (n = 127) were identified by visual signs and removed from production pens for further examination. Control animals displaying no visual signs of BRD (n = 143) were also removed and examined. Blood, nasal swab samples, and clinical measurements were collected. Lung and pleural lesions indicative of BRD were scored at slaughter. LCA was applied to identify possible outcome groups. Three latent classes were identified in the best model fit, categorized as non-BRD, mild BRD, and severe BRD. Animals in the mild BRD group had a higher probability of having visual signs of BRD compared with non-BRD and severe BRD animals. Animals in the severe BRD group were more likely to require more than 1 treatment for BRD and have ≥40 °C rectal temperature, ≥10% total lung consolidation, and severe pleural lesions at slaughter. Animals in the severe BRD group were also more likely to be naïve at feedlot entry and the first BRD pull for Bovine Viral Diarrhoea Virus, Bovine Parainfluenza 3 Virus, and Bovine Adenovirus and have a positive nasal swab result for Bovine Herpesvirus Type 1 and Bovine Coronavirus. Animals with severe BRD had 0.9 and 0.6 kg/d lower overall ADG (average daily gain) compared with non-BRD animals and mild BRD animals (P < 0.001). These results demonstrate that there are important indicators of BRD severity. Using this information to predict an animal’s BRD outcome would greatly enhance treatment efficacy and aid in better management of animals at risk of suffering from severe BRD.
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A prior study reported 95% accuracy for blood metabolome analysis with a smaller sample size of 50 BRD animals and ten controls.
“This accuracy rate is marginally lower than the 95% reported in a prior study, which had a smaller sample size consisting of 50 BRD animals and ten controls [201,202].”
From Strategies for Bovine Respiratory Disease (BRD) Diagnosis and Prognosis: A Comprehensive Overview (2024) · cites this paper as [202]
The Materials and Methods section describes 127 cattle with visual signs of BRD and 143 visually healthy controls, not 50 BRD animals and ten controls. The paper analyzes BRD outcomes using latent class analysis and describes blood testing for viral antibodies; it does not report 95% accuracy for blood metabolome analysis. (LLM, conf=0.86)
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- Authors
- Blakebrough-Hall, C., Hick, P., & González, L. A.
- Affiliations
- The University of Sydney (AU)
- Corresponding author
- Blakebrough-Hall, Claudia
- Venue
- Journal of Animal Science
- Publisher
- Oxford University Press (OUP)
- Published
- 2020-11-28
- Volume
- 98
- Issue
- 12
- ISSN
- 0021-8812 (ISSN-L)
- 1525-3163
- PMC
- PMC7755173
- OpenAlex
- W3107256628
- Cited by
- 10
- References
- 30
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 2 · 2023: 2 · 2022: 1 · 2021: 3
- FWCI
- 1.09
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Licence
- academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
- Locations
- Journal of Animal Science (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Immunology and Microbiology › Microbiology › Microbial infections and disease research
- Health Sciences › Veterinary › Small Animals › Animal health and immunology
- Life Sciences › Agricultural and Biological Sciences › Agronomy and Crop Science › Animal Disease Management and Epidemiology
- Keywords
- bovine respiratory disease, feedlot cattle, disease outcome prediction, latent class analysis, lung consolidation, pleural lesions, rectal temperature, bovine viral diarrhea virus, bovine parainfluenza virus type 3, bovine adenovirus, bovine herpesvirus 1, bovine coronavirus, average daily gain
- MeSH terms
- Latent Class Analysis, Animals, Auscultation, Body Temperature, Cattle, Diagnosis, Computer-Assisted, Lung, Male, Nasal Mucosa, New South Wales, Cohort Studies, Treatment Outcome, Bovine Respiratory Disease Complex
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