Literature DB >> 15053363

The sensitivity of gross necropsy, caudal fold and comparative cervical tests for the diagnosis of bovine tuberculosis.

Bo Norby1, Paul C Bartlett, Scott D Fitzgerald, Larry M Granger, Colleen S Bruning-Fann, Diana L Whipple, Janet B Payeur.   

Abstract

Bovine tuberculosis (bTb) was diagnosed in 22 cattle herds in the northeast comer of Michigan's lower peninsula. Of these 22 herds, 494 animals in 7 herds were examined by gross necropsy, histopathologic exam, mycobacterial culture, and polymerase chain reaction (PCR) assay performed only on samples that were histologically compatible for bTb. Results of culture and PCR assay interpreted in parallel were used as the reference test for calculation of the sensitivity of 1) the caudal fold test (CFT), 2) the caudal fold and comparative cervical skin tests used in series (CFTCCTSER), and 3) gross necropsy. Mycobacterium bovis was isolated from 43 animals. Using all 7 herds, the sensitivities of the CFT, the CFTCCTSER, and gross necropsy were 93.02%, 88.37%, and 86.05%, respectively. When the data were stratified by low- and moderate-prevalence herds, the sensitivities were 83.33%, 75.0%, and 83.33% in low-prevalence herds and 96.77%, 93.55%, and 87.10% in moderate-prevalence herds. The sensitivities of the 2 skin tests were slightly higher when 2 or more gross lesions were present, and the sensitivity of gross necropsy was significantly higher (P = 0.049). The sensitivity of the CFT was found to be notably higher than most estimates in other studies; however, a direct comparison was not possible because the amount of purified protein derivative and the reference methods were different in this study compared with other published studies. Although the sensitivities are high, 2 of the 7 herds (29%) would have had 1 or more positive animals left in the herd if a test-and-removal program had been used. This suggests that when positive herds are identified, selective culling of skin test reactors is a less acceptable disease control strategy than is complete depopulation.

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Year:  2004        PMID: 15053363     DOI: 10.1177/104063870401600206

Source DB:  PubMed          Journal:  J Vet Diagn Invest        ISSN: 1040-6387            Impact factor:   1.279


  13 in total

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2.  Performance of Loop-Mediated Isothermal Amplification Technique in Milk Samples for the Diagnosis of Bovine Tuberculosis in Dairy Cattle Using a Bayesian Approach.

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3.  Appraisal of interpretation criteria for the comparative intradermal tuberculin test for diagnosis of tuberculosis in cattle in central Ethiopia.

Authors:  Gobena Ameni; Glyn Hewinson; Abraham Aseffa; Douglas Young; Martin Vordermeier
Journal:  Clin Vaccine Immunol       Date:  2008-05-21

4.  Hui and Walter's latent-class model extended to estimate diagnostic test properties from surveillance data: a latent model for latent data.

Authors:  Mairead L Bermingham; Ian G Handel; Elizabeth J Glass; John A Woolliams; B Mark de Clare Bronsvoort; Stewart H McBride; Robin A Skuce; Adrian R Allen; Stanley W J McDowell; Stephen C Bishop
Journal:  Sci Rep       Date:  2015-07-07       Impact factor: 4.379

5.  Risk factors for bovine tuberculosis in low incidence regions related to the movements of cattle.

Authors:  M Carolyn Gates; Victoriya V Volkova; Mark E J Woolhouse
Journal:  BMC Vet Res       Date:  2013-11-09       Impact factor: 2.741

6.  Descriptive Epidemiology and Whole Genome Sequencing Analysis for an Outbreak of Bovine Tuberculosis in Beef Cattle and White-Tailed Deer in Northwestern Minnesota.

Authors:  Linda Glaser; Michelle Carstensen; Sheryl Shaw; Suelee Robbe-Austerman; Arno Wunschmann; Dan Grear; Tod Stuber; Bruce Thomsen
Journal:  PLoS One       Date:  2016-01-19       Impact factor: 3.240

7.  Evaluating diagnostic tests for bovine tuberculosis in the southern part of Germany: A latent class analysis.

Authors:  Valerie-Beau Pucken; Gabriela Knubben-Schweizer; Dörte Döpfer; Andreas Groll; Angela Hafner-Marx; Stefan Hörmansdorfer; Carola Sauter-Louis; Reinhard K Straubinger; Pia Zimmermann; Sonja Hartnack
Journal:  PLoS One       Date:  2017-06-22       Impact factor: 3.240

8.  Using machine learning improves predictions of herd-level bovine tuberculosis breakdowns in Great Britain.

Authors:  K Stański; S Lycett; T Porphyre; B M de C Bronsvoort
Journal:  Sci Rep       Date:  2021-01-26       Impact factor: 4.379

9.  Asymptomatic cattle naturally infected with Mycobacterium bovis present exacerbated tissue pathology and bacterial dissemination.

Authors:  Álvaro Menin; Renata Fleith; Carolina Reck; Mariel Marlow; Paula Fernandes; Célso Pilati; André Báfica
Journal:  PLoS One       Date:  2013-01-09       Impact factor: 3.240

10.  Towards risk-based test protocols: estimating the contribution of intensive testing to the UK bovine tuberculosis problem.

Authors:  Jan van Dijk
Journal:  PLoS One       Date:  2013-05-22       Impact factor: 3.240

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