Diagnostic accuracy of a milk pregnancy-associated glycoprotein ELISA accounting for day since last breeding for pregnancy detection in Holstein cows.

Tests detecting pregnancy-associated glycoproteins (PAG) are widely used for pregnancy diagnosis in dairy cows. Recently, a days-since-last-breeding (DSLB)-specific interpretation algorithm was proposed to account for known fluctuations in PAG concentrations during early gestation. Our objective was to evaluate the diagnostic accuracy and predictive values of this DSLB-specific interpretation for a milk-based commercially available pregnancy test (milk PAG-ELISA) compared with the manufacturer's uniform interpretation thresholds. Data were assembled from two published diagnostic validation studies conducted in Canada and South Africa, including 1260 Holstein cows from 24 commercial dairy herds tested between 28 and 50 DSLB. Milk PAG-ELISA results from manually collected samples were compared with veterinary ultrasonography examinations. Diagnostic accuracy was estimated using a Bayesian latent class model accounting for the imperfect nature of both tests and allowing accuracy to vary across DSLB intervals. When compared with the manufacturer's interpretative thresholds, the DSLB-specific grid improved PAG-ELISA specificity and positive predictive value for cows tested between 41 and 50 DSLB (+12 and +7 %age-point increases, respectively), while yielding similar accuracy for cows tested between 28 and 40 DSLB. However, pregnancy diagnosis in the 41-50 DSLB interval showed lower overall accuracy and predictive values regardless of the interpretation approach used, likely reflecting the physiological decline in PAG concentrations during that stage of gestation. These findings support the use of the novel interpretation grid to improve test performance between 41 and 50 DSLB and indicate that the accuracy of pregnancy diagnosis using milk PAG-ELISA was greater between 28 and 40 DSLB.