Diagnosis and management of bovine respiratory disease

Abstract

Bovine respiratory disease (BRD) is the most costly disease of cattle in US feedyards and diagnosis based on clinical signs of illness is challenging. Over the course of five independent studies we evaluated the precision of multiple observers assigning clinical illness scores (CIS) to calves with induced Mycoplasma bovis pneumonia. We also evaluated the accuracy of CIS in relation to lung lesions at necropsy. Agreement among observers over all five studies was slight ({kappa]= 0.16; 95% confidence interval, 0.10 to 0.24) and ranged from 0.10 to 0.21 for individual trials. The accuracy of CIS varied based on the pulmonary consolidation score chosen to represent a truly ill animal. Inflammation associated with BRD can lead to significant pulmonary damage and reduced lung function. Treatment for BRD frequently involves antimicrobial administration and occasionally non-steroidal anti-inflammatory drugs. We evaluated how calves experimentally challenged with Mannheimia haemolytica respond to treatment with flunixin meglumine, alone or in combination with the antimicrobial florfenicol. Individual calf response to bacterial pneumonia was highly variable in this study. None of the changes in serum biomarkers, CBC or chemistry parameters provided reliable indicators of the pulmonary inflammation associated with the mild severity of bronchopneumonia in our study. Metaphylaxis is frequently administered to manage the risk of BRD within cohorts of cattle. We evaluated the impact of metaphylactic antimicrobial administration 10 days prior to experimental Mannheimia haemolytica inoculation to mitigate pulmonary lesions. We found that calves receiving tildipirosin had less lung damage and fewer clinical signs of illness compared to calves treated with tulathromycin or saline. Finally, the ability to predict those animals that would not finish the production cycle normally would provide benefits in effectively managing cattle. We evaluated the ability of classification algorithms to accurately predict an individual calf’s outcome based on data available at first identification of and treatment for BRD. We found accuracy of classifiers was dependent on the data recorded by the feedyard and there are sub-groups of calves within feedyard populations where classifiers were highly accurate. These data suggest the importance of pairing the proper classifier with the data available.