The objective of this study was to develop prediction models for the serum IgG concentration in critically ill calves based on indirect assays and to assess if the predictive ability of the models could be improved by inclusion of age, clinical covariates, and/or laboratory covariates. Seventy-eight critically ill calves between 1 and 13 days old were selected from 1 farm. Statistical models to predict IgG concentration from the results of the radial immunodiffusion test, the gold standard, were built as a function of indirect assays of serum and plasma protein concentrations, zinc sulfate (ZnSO4) turbidity and transmittance, and serum g-glutamyl transferase (GGT) activity. For each assay 4 models were built: without covariates, with age, with age and clinical covariates (infection and dehydration status), and with age and laboratory covariates (fibrinogen concentration and packed cell volume). For the protein models, dehydration status (clinical model) and fibrinogen concentration (laboratory model) were selected for inclusion owing to their statistical significance. These variables increased the coefficient of determination (R2) of the models by $ 7% but did not significantly improve the sensitivity or specificity of the models to predict passive transfer with a cutoff IgG concentration of 1000 mg/dL. For the GGT assay, including age as a covariate increased the R2 of the model by 3%. For the ZnSO4 turbidity test, none of the covariates were statistically significant. Overall, the R2 of the models ranged from 34% to 62%. This study has provided insight into the importance of adjusting for covariates when using indirect assays to predict IgG concentration in critically ill calves. Results also indicate that ZnSO4 transmittance and turbidity assays could be used advantageously in a field setting.
|Original language||English (US)|
|Number of pages||6|
|Journal||Canadian Journal of Veterinary Research|
|State||Published - Apr 1 2013|
ASJC Scopus subject areas