Reproductive tract disease in Irish grazing dairy cows: Retrospective observational study examining its association with reproductive performance and accuracy of 2 diagnostic tests.

The detection of reproductive tract disease (RTD) 3 wk postpartum is important because of its effect on subsequent reproductive outcomes. Numerous methods for the diagnosis of RTD are described, some of which are more practical and instantaneous in terms of diagnosis. Two of these methods involve identification of purulent vaginal discharge (PVD) and evidence of ultrasonographic uterine changes indicative of endometritis (UE). The objectives of our retrospective observational study were (1) to assess the association of PVD or UE score at the prebreeding examination (PBE) with the hazard of pregnancy within the subsequent breeding season; (2) to determine the test sensitivity (Se) and specificity (Sp) at the point of sampling of both tests using a Bayesian latent class model; and (3) to determine the effect of varying positivity thresholds on test accuracy. To achieve these objectives, we analyzed an initial data set of 5,049 PBE from 2,460 spring-calved cows in 8 herds between 2014 and 2018. Each PBE was conducted once between 25 and 86 d in milk. At each PBE, vaginal discharge was obtained with a Metricheck device (Simcro) whereas uterine contents were assessed using transrectal ultrasonography. Purulent vaginal discharge was scored on a scale of 0 to 3 depending on discharge character, and UE was scored on a scale of 0 to 4 depending on the presence and consistency of intraluminal fluid. Cows with scores of ≥2 in either test had received treatment. Fertility data were available from 4,756 PBE after data exclusion. The association between PVD or UE score at the PBE and subsequent hazard of pregnancy was analyzed using a Cox proportional hazards model. Cows with a PVD score of 2 or 3 were less likely to conceive than cows with a PVD score 0 [score 2 hazard ratio (HR) = 0.74; 95% confidence interval (CI): 0.59-0.94; score 3 HR = 0.65; 95% CI: 0.51-0.84]. Cows with a UE score of 1, 2, 3, or 4 were less likely to conceive than cows with a UE score of 0 (score 1 HR = 0.82; 95% CI: 0.73-0.93; score 2 HR = 0.79; 95% CI: 0.62-1.00; score 3 HR = 0.43; 95% CI: 0.43-0.90; score 4 HR = 0.39; 95% CI: 0.26-0.58). To determine the Se and Sp of PVD or UE score for diagnosis of RTD at the time of PBE, a Bayesian latent class model was fitted on 2,460 individual cow PBE. Flat priors were used for the Se and Sp of UE, whereas informative priors were used for PVD Se (mode = 65%, 5th percentile = 45%) and Sp (mode = 90%, 5th percentile = 80%) and RTD prevalence (mode = 20%, 5th percentile = 10%). Posterior estimates (median and 95% Bayesian probability intervals; BPI) were obtained using 'rjags' (R Studio). The optimal test thresholds (PVD and UE score ≥1) were selected by assessing the effect of different thresholds on test estimates and using a misclassification cost analysis. Based on these, median (95% BPI) Se for PVD and UE score ≥1 were 44% (29-60%) and 67% (33-100%), respectively. Median Sp for PVD and UE score ≥1 were 90% (86-93%) and 91% (86-93%), respectively. Higher scores in both tests were associated with impaired fertility, and UE scoring with a threshold of ≥1 had the highest test Se and Sp estimates although test Se was conditional on days in milk when the PBE occurred.

Estimation of the true prevalence of inaccurate artificial inseminations in Irish milk recording dairy cows using a Bayesian latent class analysis.

Inaccurate artificial insemination (IAI) refers to an artificial insemination (AI) that is performed when a cow is not in oestrus. IAIs have economic impacts on the dairy industry through of semen wastage or iatrogenic pregnancy loss. However, few studies have quantified the prevalence of IAIs in a population. The primary objective of this prospective study was to estimate the cow-level true prevalence of IAIs in Irish milk recording dairy herds using a latent class model with a Bayesian framework. Milk samples were collected at a milk recording laboratory from 576 dairy cows in 125 herds who had received an AI on the same day they were sampled for routine milk constituent analysis. Milk progesterone (MP4) analysis was conducted on these samples using radioimmunoassay to determine the progesterone concentration. Fertility data (i.e., subsequent calving date) was retrospectively obtained from the Irish National Cattle Breeding Federation for milk sampled cows and an apparent conception (AC) to the sample AI was determined based on an estimated gestational range of 270-290 days. Both tests (MP4 and AC) were used in a latent class model to estimate the true prevalence of IAI. For the MP4 test, a concentration of ≥ 5 ng/mL in whole milk was deemed to be test positive while for the AC test, a cow that did not conceive to the sampled AI was deemed test positive. Prior information for prevalence of IAI was obtained from a literature review while MP4 sensitivity (Se) and specificity (Sp) were obtained from expert opinion. Non-informative priors were used for the Se and Sp of the AC test. Posterior inferences (median and 95 % Bayesian probability intervals; BPI) were obtained using the 'rjags' package in the R statistical software. In the final model, median cow-level true prevalence of IAI was 4.4 % (BPI; 1.7-9.0 %). Median Se and Sp estimates for MP4, were 83.0 % (BPI; 65.0-96.2 %) and were 97.4 % (BPI; 94.6-99.6 %), respectively. Median Se and Sp estimates for AC, were 64.8 % (BPI; 44.5-88.6 %) and 49.8 % (BPI; 45.3-54.1 %), respectively. The present study estimates that the overall cow-level true prevalence of IAI in Irish dairy cows is relatively low. This is the first study to report the cow-level true prevalence of IAI using a Bayesian latent class model.

The effect of dairy heifer pre-breeding growth rate on first lactation milk yield in spring-calving, pasture-based herds.

Optimising heifer growth rate may offer an opportunity to improve lifetime milk yield per cow, enhancing the environmental and economic efficiency of dairy farming operations. The effect of dairy heifer pre-breeding average daily weight gain (ADGPB) on first lactation milk yield was investigated. This observational study employed a data set comprising 265 Holstein-Friesian, or Holstein-Friesian-cross-Jersey heifers from seven commercial, spring-calving, pasture-based dairy herds, where the major component of the diet was grazed grass. These were weighed at birth and prior to breeding and ADGPB was calculated. Milk recordings were performed throughout the heifers' first lactation and 305-day yield figures calculated from these records. Yields were corrected to 4% fat and 3.1% protein to create standardised 305-day milk yield (SMY), which was the outcome of interest. Median ADGPB was 0.72 kg/day. Median 305-day yield was 5 967 kg. Linear regression was used to investigate the effect of weight and genetic, age and first calving factors on SMY. Pre-breeding average daily weight gain, age at first calving and predicted transmitting abilities for milk protein production and calving interval were all significant in the final model, which also included the random effects of farm and month of calving within year. ADGPB was quadratically related to first lactation SMY, with an ADGPB of 0.82 kg/day corresponding to the maximum predicted SMY. The model predicted that a heifer growing at 0.82 kg/day would produce 1 120 kg more SMY than a heifer growing at 0.55 kg/day, 218 kg more than a heifer growing at 0.7 kg/day and 103 kg more than a heifer growing at 0.90 kg/day. Manipulation of heifer growth rate may offer a viable method of increasing first lactation milk yield.

Comparative Utility of Manual versus Automated Segmentation of Hippocampus and Entorhinal Cortex Volumes in a Memory Clinic Sample.

Structural neuroimaging is a useful non-invasive biomarker commonly employed to evaluate the integrity of mesial temporal lobe structures that are typically compromised in Alzheimer's disease. Advances in quantitative neuroimaging have permitted the development of automated segmentation protocols (e.g., FreeSurfer) with significantly increased efficiency compared to earlier manual techniques. While these protocols have been found to be suitable for large-scale, multi-site research studies, we were interested in assessing the practical utility and reliability of automated FreeSurfer protocols compared to manual volumetry on routinely acquired clinical scans. Independent validation studies with newer automated segmentation protocols are scarce. Two FreeSurfer protocols for each of two regions of interest-the hippocampus and entorhinal cortex-were compared against manual volumetry. High reliability and agreement was found between FreeSurfer and manual hippocampal protocols, however, there was lower reliability and agreement between FreeSurfer and manual entorhinal protocols. Although based on a the relatively small sample of subjects drawn from a memory clinic (n = 27), our study findings suggest further refinements to improve measurement error and most accurately depict true regional brain volumes using automated segmentation protocols are required, especially for non-hippocampal mesial temporal structures, to achieve maximal utility for routine clinical evaluations.

Medicaid's beta 2-agonist recipients and their treatment by national standards.

OBJECTIVE: To determine whether Connecticut's Medicaid high-dose beta 2-agonists (HDB) users (> 1 canister/mo) are receiving medications according to National Institutes of Health (NIH) asthma guidelines, and to compare healthcare utilization between HDB users and patients receiving no more than one canister of a short-acting beta 2-agonist per month. METHODS: All Connecticut Medicaid pharmacy claims from April to December 1998 were examined. Subjects were included if they had an asthma diagnosis and were excluded if they had chronic obstructive pulmonary disease. The percentage of HDB users not receiving long-term-control medication; receiving low doses of a long-term-control medication; and receiving oral, nebulized, or long-acting beta 2-agonists was determined. Healthcare utilization between HDB users and patients receiving no more than one canister of a short-acting beta 2-agonist per month was also compared. RESULTS: Of 1599 profiles included, 14% (n = 223) were HDB users. Twenty-five percent of these patients did not receive a long-term-control medication, and 35% received low doses of a long-term-control medication. Claims for oral, nebulized, and long-acting beta 2-agonists were submitted for 4%, 29%, and 22% of HDB users, respectively. More claims for short courses of oral corticosteroids were submitted for HDB users than for patients receiving no more than one canister of a short-acting beta 2-agonist per month (n = 1376) (1.99 +/- 3.60 vs. 0.39 +/- 1.07 mean +/- SD; p < 0.001). HDB users visited their physicians' offices an average of 4.72 +/- 24.08 times per month compared with an average of 2.40 +/- 14.4 office visits per month for patients receiving no more than one canister of a short-acting beta 2-agonist (p = 0.04). CONCLUSIONS: A high proportion of Connecticut's Medicaid HDB users are not receiving medications according to NIH guidelines. HDB users were significantly more likely to receive short courses of oral corticosteroids and required significantly more office visits than patients receiving no more than one canister of a short-acting beta 2-agonist per month. Intervention programs designed to improve adherence to the guidelines will be developed.

An examination of the effect of market demographic and competitive characteristics on gross margins of prescription drugs.

This study was carried out to determine the influence of selected demographic and competitive market factors on community pharmacy operations. Data were collected from a panel of pharmacies located in large mid-western city. A sample of 300 prescriptions was obtained from each of the panel pharmacies. From the prescriptions, the gross margins and the addresses of the patrons were determined. A profile of the demographic and competitive factors was determined. Eight research hypotheses were tested. The variables were subjected to regression analysis with per cent markup and dollar markup-on-retail being the dependent variables in each case. The simple regression analysis did reflect a significant relationship between select competitive variables and per cent markup. The stepwise regressions indicated a significant relationship between all demographic and competitive market factors and per cent markup. No significant relationships were found in the simple regression treatment of a dollar markup and the market variables. The stepwise regression routine yielded a nonsignificant relationship between dollar markup and all market variables except income and education. It can be concluded that pricing in this market is reflective of both demographic and competitive market factors of the trading area.