Evaluation of inter-observer agreement when using a clinical respiratory scoring system in pre-weaned dairy calves. Issue 4 (3rd July 2016) - Buczinski, S; Faure, C; Jolivet, S; Abdallah, A
Abstract: AIM: To determine inter-observer agreement for a clinical scoring system for the detection of bovine respiratory disease complex in calves, and the impact of classification of calves as sick or healthy based on different cut-off values. METHODS: Two third-year veterinary students (Observer 1 and 2) and one post-graduate student (Observer 3) received 4 hours of training on scoring dairy calves for signs of respiratory disease, including rectal temperature, cough, eye and nasal discharge, and ear position. Observers 1 and 2 scored 40 pre-weaning dairy calves 24 hours apart (80 observations) over three visits to a calf-rearing facility, and Observers 1, 2 and 3 scored 20 calves on one visit. Inter-observer agreement was assessed using percentage of agreement (PA) and Kappa statistics for individual clinical signs, comparing Observers 1 and 2. Agreement between the three observers for total clinical score was assessed using cut-off values of ≥4, ≥5 and ≥6 to indicate unhealthy calves. RESULTS: Inter-observer PA for rectal temperature was 0.68, for cough 0.78, for nasal discharge 0.62, for eye discharge 0.63, and for ear position 0.85. Kappa values for all clinical signs indicated slight to fair agreement (<0.4), except temperature that had moderate agreement (0.6). The Fleiss' Kappa for total score, using cut-offs of ≥4, ≥5 and ≥6 to indicate unhealthy calves, was 0.35, 0.06 and 0.13, respectively, indicating slight to fair agreement. CONCLUSIONS AND CLINICAL RELEVANCE: There was important inter-observer discrepancies in scoring clinical signs of respiratory disease, using relatively inexperienced observers. These disagreements may ultimately mean increased false negative or false positive diagnoses and incorrect treatment of cases. Visual assessment of clinical signs associated with bovine respiratory disease needs to be thoroughly validated when disease monitoring is based on the use of a clinical scoring system.