Comparative efficacy of blanket versus selective dry-cow therapy: a systematic review and pairwise meta-analysis
Bibliographic record
Abstract
A systematic review and meta-analysis were conducted to determine the efficacy of selective dry-cow antimicrobial therapy compared to blanket therapy (all quarters/all cows). Controlled trials were eligible if any of the following were assessed: incidence of clinical mastitis during the first 30 DIM, frequency of intramammary infection (IMI) at calving, or frequency of IMI during the first 30 DIM. From 3480 identified records, nine trials were data extracted for IMI at calving. There was an insufficient number of trials to conduct meta-analysis for the other outcomes. Risk of IMI at calving in selectively treated cows was higher than blanket therapy (RR = 1.34, 95% CI = 1.13, 1.16), but substantial heterogeneity was present (I2 = 58%). Subgroup analysis showed that, for trials using internal teat sealants, there was no difference in IMI risk at calving between groups, and no heterogeneity was present. For trials not using internal teat sealants, there was an increased risk in cows assigned to a selective dry-cow therapy protocol, compared to blanket treatment, with substantial heterogeneity in this subgroup. However, the small number of trials and heterogeneity in the subgroup without internal teat sealants suggests that the relative risk between treatments may differ from the determined point estimates based on other unmeasured factors.
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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 | 0.014 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.035 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".