Randomized clinical trial of antibiotic and prostaglandin treatments for uterine health and reproductive performance in dairy cows
Bibliographic record
Abstract
The objectives of this study were to assess the efficacy of antibiotic treatment for preventing postpartum uterine disease among cows at high risk of uterine disease, and to assess the efficacy of PGF(2α) for treating cytological endometritis (CYTO) and purulent vaginal discharge (PVD). A total of 2,178 Holstein cows in 6 herds were enrolled in a randomized clinical trial. Within 24h after parturition, cows were classified at being at high risk of uterine disease (HRUD; n=1,017) if they had twins, dystocia, or retained placenta. All remaining cows were classified as being at low risk of uterine disease (LRUD; n=1,161). Cows in the HRUD group were randomly allocated in a factorial design to receive ceftiofur crystalline free acid (CCFA) at 24h after parturition or be untreated, and to receive dinoprost (PGF(2α)) at 35 and 49 (±3) days in milk (DIM) or to be untreated. Cows in LRUD were randomly allocated to receive PGF(2α) at 35 and 49 (±3) DIM or to be untreated. Serum progesterone was measured at 21, 35, 49, and 63 (±3) DIM. Cows were examined at 35 (±3; exam 1) and 56 (±3; exam 2) DIM for CYTO (by cytobrush device; ≥6% polymorphonuclear cells in endometrial cytology) and for PVD (by Metricheck device; mucopurulent or purulent vaginal discharge). Statistical analyses were performed using multivariable logistic regression models accounting for herd clustering. Treatment with CCFA in HRUD cows was not associated with the probability of metritis overall, but interactions occurred such that CCFA decreased the incidence of metritis among HRUD cows that did not have retained placenta and among cows of parity ≥2. Treatment with CCFA in HRUD cows decreased the probability of PVD at exam 1. Treatment with PGF(2α) did not affect the probability of cure of CYTO or PVD irrespective of progesterone concentration at the time of treatment. Among cows affected by CYTO or PVD at exam 1, 66 and 63%, respectively, had spontaneously cured at exam 2. Cows persistently affected at exam 2 had an increased time to pregnancy and were more likely to have both CYTO and PVD at exam 1. Administration of PGF(2α) at both 5 and 7 wk postpartum did not mitigate the effects of CYTO or PVD on reproductive performance. Clinical approaches to treatment of chronic postpartum reproductive tract infection and inflammation should be reassessed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".