Performance of various interpretations of clinical scoring systems for diagnosis of respiratory disease in dairy calves in a temperate climate using Bayesian latent class analysis.

Bovine respiratory disease (BRD) presents a challenge to farmers all over the globe not only because it can have significant impacts on welfare and productivity, but also because diagnosis can prove challenging. Several clinical scoring systems have been developed to aid farmers in making consistent early diagnosis, 2 examples being the Wisconsin (WCS) and the California (CALIF) systems. Neither of these systems were developed in or for use in a temperate environment. As environment may lead to changes in BRD presentation, the weightings and cut offs designed for one environmental presentation of BRD may not be appropriate when used in a temperate climate. Additionally, the interpretation of the scores recorded varies between studies; this may also influence conclusions. Hence, the objective of this work was to investigate the sensitivity (Se) and specificity (Sp) of these tests in a temperate climate and investigate the influence of varying the interpretation on the performance of the WCS. In this prospective study, 98 commercial spring calving dairy farms were recruited (40 randomly, 58 targeted) and visited. Thoracic ultrasound and WCS was performed on 20 randomly sampled calves between 4 and 6 weeks of age on each farm. On a subset of 32 farms, the CALIF score was also undertaken. The data were then used in a hierarchical Bayesian latent class model to estimate the Se and Sp of 5 different interpretations of the Wisconsin clinical score and one interpretation of the California clinical score. In total, 1,936 calves were examined. The Se of the Wisconsin score varied from 0.336 to 0.577 depending on the interpretation used and the Sp varied from 0.943 to 0.977. The Se of the California score was 0.529 (95% Bayesian credible interval (BCI); 0.403, 0.651) and the Sp was 0.903 (95% bci; 0.883, 0.922). In conclusion, the performance of the clinical scores in a temperate environment were similar to previously published work from more extreme climates, however the performance varied widely depending on the score interpretation. Authors should justify their usage of a particular clinical score interpretation to improve clarity in publications.