Short communication: Efficacy of a second intrauterine cephapirin infusion for the treatment of purulent vaginal discharge and endometritis in postpartum dairy cows
Bibliographic record
Abstract
The objective of this study was to quantify the efficacy of a second intrauterine cephapirin treatment administered 14 d after the initial one on subsequent reproductive performance of postpartum dairy cows affected by purulent vaginal discharge (PVD) or endometritis (ENDO). In total, 4,140 Holstein cows from 30 commercial herds were enrolled in a randomized clinical trial. At 36 (±7) d in milk, cows were examined using the Metricheck device to diagnose PVD. An endometrial cytology sample was also collected from each cow to perform a leukocyte esterase test for diagnosing ENDO. Diagnosis of PVD and ENDO was done cow-side. Cows diagnosed with PVD or ENDO were assigned to receive 1 of 2 treatments: (1) a single intrauterine cephapirin infusion (500 mg of cephapirin benzathin; Metricure, Merck Animal Health, Kirkland, QC, Canada) at the time of initial examination or (2) a single intrauterine infusion at the time of initial examination and a second one 14 d later. Subsequent reproductive and culling events were collected until 200 d in milk. Statistical analyses were performed using univariable and multivariable mixed logistic regression models. In cows affected by PVD, a second intrauterine cephapirin infusion increased the pregnancy risk at first insemination in comparison with cows that only received one treatment (28.0 vs. 38.8%). In cows affected by ENDO, a second treatment also increased the pregnancy risk at first insemination compared with cows that only received one treatment (30.3 vs. 39.2%). Overall, these results demonstrate that administering a second intrauterine cephapirin infusion 14 d after the initial treatment in postpartum cows affected by PVD or ENDO did improve their subsequent reproductive performance.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".