Validation of a clinical scoring system for bovine respiratory disease complex diagnosis in preweaned dairy calves using a Bayesian framework.

ABSTRACT: Bovine respiratory disease complex is a major cause of illness in dairy calves. The diagnosis of active infection of the lower respiratory tract is challenging on daily basis in the absence of accurate clinical signs. Clinical scoring systems such as the Californian scoring system, are appealing but were developed without considering the imperfection of reference standard tests used for case definition. This study used a Bayesian latent class model to update Californian prediction rules. The results of clinical examination and ultrasound findings of 608 preweaned dairy calves were used. A model accounting for imperfect accuracy of thoracic ultrasound examination was used to obtain updated weights for the clinical signs included in the Californian scoring system. There were 20 points (95% B

SUBMITTER: Buczinski S 

PROVIDER: S-EPMC7114123 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature