Bayesian accuracy estimates and fit for purpose thresholds of cytology and culture of endometrial swab samples for detecting endometritis in mares.

The overall aim of this work was to identify the potential impact of misclassification errors associated with routine screening and diagnostic testing for endometritis in mares. Using Bayesian latent class models (BLCM), specific objectives were to: 1) estimate the diagnostic accuracy of cytology and culture of endometrial swab samples to detect endometritis in mares; 2) assess the impact of different cytology thresholds on test accuracy and misclassification costs; and 3) assess the sensitivity (Se) and specificity (Sp) of a diagnostic strategy including both tests interpreted in series and parallel. Diagnostic and pre-breeding endometrial swab samples collected from 3448 mares based at breeding premises located in the South East of England between 2014 and 2020 were retrospectively analysed. Culture results were classified as positive according to three different case definitions: (A) > 90% of the growth colonies were a monoculture; (B) pathogenic or pathogenic and non-pathogenic bacteria were identified; and (C) any growth was observed. Endometrial smears were graded based on the percent of polymorphonuclear cells (PMN) per high power field (HPF). A hierarchical BLCM was fitted using the cross-tabulated results of the three culture case definitions with a cytology threshold fixed at > 0.5% PMN. Fit for purpose cytology thresholds were proposed using a misclassification cost analysis in the context of good antimicrobial stewardship and for varying endometritis prevalence estimates. Median [95% Bayesian credible intervals (BCI)] cytology Se estimates were 6.5% (2.2-11.6), 6.4% (2.2-10.8) and 6.3% (2.2-10.8) for scenario A, B and C, respectively. Median (95% BCI) cytology Sp estimates were 88.8% (83.1-94.8), 88.9% (83.9-93.8) and 88.8% (84.0-93.8) for scenarios A, B and C, respectively. Median (95% BCI) culture Se estimates were 37.5% (29.9-46.0), 42.3% (33.8-51.1) and 46.4% (35.7-55.9) for scenarios A, B and C, respectively. Median (95% BCI) culture Sp estimates were 92.8% (84.3-99.0), 91.5% (82.5-98.0) and 90.8% (80.1-97.4) for scenarios A, B and C, respectively. Regardless of the culture case definition, Se and Sp of cytology (> 0.5% PMN) was lower than previously reported for swab samples in studies using histology as the reference standard test. The misclassification cost term decreased as the cytology threshold increased for all scenarios and all prevalence contexts, suggesting that, regardless of the endometritis prevalence in the population, increasing the cytology threshold would reduce the misclassification costs associated with false positive mares contributing to good antimicrobial stewardship.

Accuracy of leukocyte esterase test, endometrial cytology and vaginal discharge score for diagnosing postpartum reproductive tract health status in dairy cows at the moment of sampling, using a latent class model fit within a Bayesian framework.

The objectives of this retrospective study were: 1) to determine the sensitivity (Se) and specificity (Sp) of leukocyte esterase test (LE), endometrial cytology (CYTO) and vaginal discharge score (VDS) for diagnosis of reproductive tract diseases in dairy cows at the moment of sampling; 2) to assess the impact of different thresholds on test accuracy and misclassification costs; and 3) to quantify herd prevalence of reproductive tract diseases in dairy farms from Québec, Canada. Data from 2092 cows (39 herds) enrolled in two randomized control trials were included. Cows were examined at 35 (± 7) days in milk using LE, CYTO, and VDS to determine their reproductive tract health status. A latent class model assuming conditional dependence of CYTO and LE was fit within a Bayesian framework. Non-informative priors were used for the Se and Sp of LE, CYTO, and VDS, while prior information for disease prevalence was obtained from expert opinions (mode = 20%, 5th percentile = 10%). Posterior inferences (median and 95% Bayesian credible intervals; BCI) were obtained using the WinBUGS statistical freeware. An initial model was built using thresholds of ≥ 1 (small amount of leukocytes), of ≥ 6%, and of ≥ 3 (mucopurulent discharge) for the LE, CYTO, and VDS, respectively. Then, the impact on tests accuracy and misclassification costs of using different thresholds was explored. Optimal thresholds balancing the need for good antimicrobial stewardship and animal health considerations were proposed. The optimal thresholds obtained in the final model were: LE ≥ 2 (moderate amount of leukocytes), CYTO ≥ 6%, and VDS ≥ 2 (mucus with flecks of pus). In the final model, median (95% BCI) Se for LE, CYTO and VDS were 42.6% (38.8-47.0), 45.9% (41.9-50.7), and 64.2% (59.1-70.3), respectively. Median Sp was 90.9% (88.0-93.6) for LE, 92.2% (89.2-94.9) for CYTO and 96.6% (91.3-99.8) for VDS. Median within-herd prevalence of reproductive tract disease was estimated at 47.9% (39.0-56.7). At a threshold ≥ 2 (mucus with flecks of pus), VDS had the highest Se and Sp among the tests evaluated. The LE is an interesting diagnostic alternative for detecting reproductive tract disease in dairy cows. At a threshold ≥ 2 (moderate amount of leukocytes), LE Se and Sp were comparable to those of CYTO. This is the first study reporting the accuracy of LE, CYTO, and VDS for diagnosing reproductive tract diseases in dairy cows at the moment of sampling.