Development of a multivariable prediction model to identify dairy calves too young to be transported to auction markets in Canada using simple physical examination and body weight

Abstract

ABSTRACT: Calves born on Eastern Canadian dairy farms that are not kept in the herds are traditionally sold through auction markets and are raised for meat purposes such as veal calves. Since February 2020, a new Canadian federal regulation has forbidden calves <9 d old to be sold through auction markets. However, in the absence of a real-time birth registry consultation system, it would be of interest to look for predictors that could be associated with age to allow identification of calves too young to be transported. In the current retrospective cross-sectional study, 1,178 calves with a declared birth date (411 calves aged <9 d old; 34.9%) were assessed in 2 large Québec auction sites. Easy-to-record covariates [body weight (BW), breed phenotype, and presence of an umbilical cord remnant] as well as other clinical signs (umbilical swelling, enlargement, umbilical pain, wet umbilicus, skin tent, sunken eyes, ocular and nasal secretion, and hide cleanliness) were assessed. Two logistic regression models using age as a dichotomous dependent variable (<9 d old vs ≥9 d old) were built. The first model (model 1) considered all covariates, which were selected after univariable analyses and a backward stepwise selection process, whereas a more pragmatic model (model 2) only included the 3 easy-to-record variables (i.e., BW, breed, umbilical cord). Both models had similar accuracy to detect calves <9 d old (sensitivity of 38.4 and 37.5%, and specificity of 85.7 and 84.6% for model 1 and 2, respectively). Model 2 was subsequently more specifically studied as it employs a faster and easier assessment. Decision thresholds were tested for their robustness based on misclassification cost term (MCT) analysis with various prevalence of calves <9 d old and various costs of false-negative:false-positive ratio. Despite statistical significance, model accuracy, even if refined with MCT analysis, was limited at the individual level, showing the limits of using physical signs and BW or their combination as a reliable proxy of age. The sensitivity of these models to find calves <9 d old was not to be used for monitoring compliance with the Canadian federal regulation. The relatively high model specificity may help to use this model as a rule-in test (i.e., targeting positive calves for further investigation) rather than a rule-out test (due to its low sensitivity).

Keywords

• surplus calves
• regulation
• fitness for transport
• diagnosis