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Cited by 113Microbial infections and disease researchAnimal health and immunologyAnimal Disease Management and Epidemiology

The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.

Diagnostic accuracy of clinical illness for bovine respiratory disease (BRD) diagnosis in beef cattle placed in feedlots: A systematic literature review and hierarchical Bayesian latent-class meta-analysis

Timsit, E., Dendukuri, N., Schiller, I., Buczinski, S.·2016·Preventive Veterinary Medicine
DOI 10.1016/j.prevetmed.2016.11.006
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Abstract

Diagnosis of bovine respiratory disease (BRD) in beef cattle placed in feedlots is typically based on clinical illness (CI) detected by pen-checkers. Unfortunately, the accuracy of this diagnostic approach (namely, sensitivity [Se] and specificity [Sp]) remains poorly understood, in part due to the absence of a reference test for ante-mortem diagnosis of BRD. Our objective was to pool available estimates of CI's diagnostic accuracy for BRD diagnosis in feedlot beef cattle while adjusting for the inaccuracy in the reference test. The presence of lung lesions (LU) at slaughter was used as the reference test. A systematic review of the literature was conducted to identify research articles comparing CI detected by pen-checkers during the feeding period to LU at slaughter. A hierarchical Bayesian latent-class meta-analysis was used to model test accuracy. This approach accounted for imperfections of both tests as well as the within and between study variability in the accuracy of CI. Furthermore, it also predicted the Se CI and Sp CI for future studies. Conditional independence between CI and LU was assumed, as these two tests are not based on similar biological principles. Seven studies were included in the meta-analysis. Estimated pooled Se CI and Sp CI were 0.27 (95% Bayesian credible interval: 0.12-0.65) and 0.92 (0.72-0.98), respectively, whereas estimated pooled Se LU and Sp LU were 0.91 (0.82-0.99) and 0.67 (0.64-0.79). Predicted Se CI and Sp CI for future studies were 0.2…

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Metadata

Authors
Timsit, E., Dendukuri, N., Schiller, I., & Buczinski, S.
Affiliations
  • University of Calgary (CA)
  • McGill University Health Centre (CA)
  • Université de Montréal (CA)
Corresponding author
Buczinski, S.
ORCID
Venue
Preventive Veterinary Medicine
Publisher
Elsevier BV
Published
2016-12
Volume
135
Pages
67-73
ISSN
0167-5877 (ISSN-L)
DOI
10.1016/j.prevetmed.2016.11.006
OpenAlex
W2552609869
Cited by
112
References
38
Citations by year
2026: 9 · 2025: 14 · 2024: 11 · 2023: 11 · 2022: 15 · 2021: 17 · 2020: 16 · 2019: 4 · 2018: 10 · 2017: 5
FWCI
0.75
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • Preventive Veterinary Medicine (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Life Sciences › Immunology and Microbiology › Microbiology › Microbial infections and disease research
  • Life Sciences › Agricultural and Biological Sciences › Animal Science and Zoology › Animal health and immunology
  • Life Sciences › Agricultural and Biological Sciences › Animal Science and Zoology › Animal Disease Management and Epidemiology
Keywords
bovine respiratory disease, beef cattle, feedlot, diagnostic accuracy, sensitivity and specificity, lung lesions, antemortem diagnosis
MeSH terms
Animals, Animal Husbandry, Bayes Theorem, Cattle, Diagnostic Techniques, Respiratory System, Female, Male, Models, Theoretical, Sensitivity and Specificity, Bovine Respiratory Disease Complex

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