Predicting bovine respiratory disease outcome in feedlot cattle using latent class analysis

• Published in: Journal of animal science Vol. 98; no. 12; pp. 1 - 10
• Main Authors: Blakebrough-Hall, Claudia, Hick, Paul, González, Luciano A
• Format: Journal Article
• Language: English
• Published: US Oxford University Press 01.12.2020
• Subjects: Animal diseases; Animal Health and Well Being; Animals; Auscultation - veterinary; Body Temperature; Bovine Respiratory Disease Complex - diagnosis; Bovine Respiratory Disease Complex - drug therapy; Bovine Respiratory Disease Complex - epidemiology; Bovine Respiratory Disease Complex - pathology; Cattle; Cohort Studies; Coronaviruses; Diagnosis, Computer-Assisted - veterinary; Diarrhea; Feedlots; Health services; Indicators; Intensive farming; Latent Class Analysis; Lesions; Lung - pathology; Lungs; Male; Nasal Mucosa - virology; New South Wales - epidemiology; Parainfluenza; Respiratory diseases; Risk management; Seroconversion; Slaughter; Studies; Temperature; Treatment Outcome; Viruses; New South Wales; predictors; severity; bovine respiratory disease; latent class analysis
• ISSN: 0021-8812; 1525-3163
• DOI: 10.1093/jas/skaa381

Abstract Bovine respiratory disease (BRD) is the most significant disease affecting feedlot cattle. Indicators of BRD often used in feedlots such as visual signs, rectal temperature, computer-assisted lung auscultation (CALA) score, the number of BRD treatments, presence of viral pathogens, viral seroconversion, and lung damage at slaughter vary in their ability to predict an animal’s BRD outcome, and no studies have been published determining how a combination of these BRD indicators may define the number of BRD disease outcome groups. The objectives of the current study were (1) to identify BRD outcome groups using BRD indicators collected during the feeding phase and at slaughter through latent class analysis (LCA) and (2) to determine the importance of these BRD indicators to predict disease outcome. Animals with BRD (n = 127) were identified by visual signs and removed from production pens for further examination. Control animals displaying no visual signs of BRD (n = 143) were also removed and examined. Blood, nasal swab samples, and clinical measurements were collected. Lung and pleural lesions indicative of BRD were scored at slaughter. LCA was applied to identify possible outcome groups. Three latent classes were identified in the best model fit, categorized as non-BRD, mild BRD, and severe BRD. Animals in the mild BRD group had a higher probability of having visual signs of BRD compared with non-BRD and severe BRD animals. Animals in the severe BRD group were more likely to require more than 1 treatment for BRD and have ≥40 °C rectal temperature, ≥10% total lung consolidation, and severe pleural lesions at slaughter. Animals in the severe BRD group were also more likely to be naïve at feedlot entry and the first BRD pull for Bovine Viral Diarrhoea Virus, Bovine Parainfluenza 3 Virus, and Bovine Adenovirus and have a positive nasal swab result for Bovine Herpesvirus Type 1 and Bovine Coronavirus. Animals with severe BRD had 0.9 and 0.6 kg/d lower overall ADG (average daily gain) compared with non-BRD animals and mild BRD animals (P < 0.001). These results demonstrate that there are important indicators of BRD severity. Using this information to predict an animal’s BRD outcome would greatly enhance treatment efficacy and aid in better management of animals at risk of suffering from severe BRD.