Bayesian assessment of diagnostic accuracy of a commercial borescope and of trimming chute exams for diagnosing digital dermatitis in dairy cows.


Journal

Journal of dairy science
ISSN: 1525-3198
Titre abrégé: J Dairy Sci
Pays: United States
ID NLM: 2985126R

Informations de publication

Date de publication:
Apr 2020
Historique:
received: 19 06 2019
accepted: 16 12 2019
pubmed: 15 2 2020
medline: 1 8 2020
entrez: 15 2 2020
Statut: ppublish

Résumé

Digital dermatitis (DD) is a worldwide infectious disease of cattle that causes lameness, discomfort, and economic losses. The reference standard test to diagnose DD is visual observation in a trimming chute, which cannot be practically performed daily on dairy farms. Moreover, some lesion misclassification may occur using this standard diagnostic method. The possibility of misclassification makes the use of a trimming chute debatable as a perfect reference standard test. The objective of this study was, therefore, to assess the diagnostic accuracy of a commercial borescope and trimming chute exam. The accuracy (sensitivity and specificity) of the tests and DD prevalence were investigated using Bayesian latent class analyses. Our hypothesis was that a commercial borescope can be routinely used to diagnose DD in a milking parlor without previous feet cleaning. A cross-sectional study was performed in a freestall facility. The lesions were scored (M0, M1, M2, M3, M4, M4.1) in the milking parlor with a borescope, followed by an examination in the trimming chute 48 to 72 h after the borescope exam. A total of 870 hind feet were scored during 2 sessions of trimming chute exams and borescope exams in the milking parlor. The data were analyzed in 2 ways. First, data were dichotomized into DD lesions (M1, M2, M3, M4, M4.1) and absence of DD lesions (M0). Second, data were dichotomized into active DD lesions (M1, M2, M4.1) and inactive lesions (M0, M3, M4). A Bayesian latent class model allowing for conditional dependence between tests was used to estimate tests' accuracy, likelihood ratio, and DD prevalence. When the data were dichotomized into DD lesions (M1-M4.1) versus absence of DD (M0) lesions, the sensitivity and specificity of the borescope was 55% [95% credible interval (CrI) 40-71%] and 81% (95% CrI 75-88%). The sensitivity of trimming chute exams was 79% (95% CrI 68-88%), and specificity was 80% (95% CrI 71-89%). When the data were dichotomized into active lesions (M1, M2, M4.1) versus inactive lesions or absence of lesions (M3, M4, M0), the sensitivity and specificity of the borescope were, respectively, 32% (95% CrI 13-58%) and 91% (95% CrI 88-95%). The sensitivity and specificity of trimming chute exams were 91% (95% CrI 81-97%) and 81% (95% CrI 75-89%), respectively. In conclusion, it is possible to use the borescope in the milking parlor without cleaning the feet to monitor prevalence of DD lesions. However, an isolated borescope examination, especially for diagnosing active DD lesions, has low sensitivity for use as a surveillance method. For such use, the sensitivity could be improved by repeating the borescope exam on a regular basis.

Identifiants

pubmed: 32057431
pii: S0022-0302(20)30101-6
doi: 10.3168/jds.2019-17129
pii:
doi:

Types de publication

Clinical Trial, Veterinary Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

3381-3391

Informations de copyright

Copyright © 2020 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Auteurs

Salvatore Ferraro (S)

Département de Sciences Cliniques, Faculté de Médecine Vétérinaire, Université de Montréal, 3200 rue Sicotte, St-Hyacinthe, Québec, J2S 2M2, Canada.

Sébastien Buczinski (S)

Département de Sciences Cliniques, Faculté de Médecine Vétérinaire, Université de Montréal, 3200 rue Sicotte, St-Hyacinthe, Québec, J2S 2M2, Canada. Electronic address: s.buczinski@umontreal.ca.

Simon Dufour (S)

Département de Pathologie et Microbiologie, Faculté de Médecine Vétérinaire, Université de Montréal, 3200 rue Sicotte, St-Hyacinthe, Québec, J2S 2M2, Canada.

Marjolaine Rousseau (M)

Département de Sciences Cliniques, Faculté de Médecine Vétérinaire, Université de Montréal, 3200 rue Sicotte, St-Hyacinthe, Québec, J2S 2M2, Canada.

Jocelyn Dubuc (J)

Département de Sciences Cliniques, Faculté de Médecine Vétérinaire, Université de Montréal, 3200 rue Sicotte, St-Hyacinthe, Québec, J2S 2M2, Canada.

Jean-Philippe Roy (JP)

Département de Sciences Cliniques, Faculté de Médecine Vétérinaire, Université de Montréal, 3200 rue Sicotte, St-Hyacinthe, Québec, J2S 2M2, Canada.

André Desrochers (A)

Département de Sciences Cliniques, Faculté de Médecine Vétérinaire, Université de Montréal, 3200 rue Sicotte, St-Hyacinthe, Québec, J2S 2M2, Canada.

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Classifications MeSH