Comparative efficacy of antimicrobial treatments in dairy cows at dry-off to prevent new intramammary infections during the dry period or clinical mastitis during early lactation: a systematic review and network meta-analysis
Bibliographic record
Abstract
A systematic review and network meta-analysis were conducted to assess the relative efficacy of antimicrobial therapy given to dairy cows at dry-off. Eligible studies were controlled trials assessing the use of antimicrobials compared to no treatment or an alternative treatment, and assessed one or more of the following outcomes: incidence of intramammary infection (IMI) at calving, incidence of IMI during the first 30 days in milk (DIM), or incidence of clinical mastitis during the first 30 DIM. Databases and conference proceedings were searched for relevant articles. The potential for bias was assessed using the Cochrane Risk of Bias 2.0 algorithm. From 3480 initially identified records, 45 trials had data extracted for one or more outcomes. Network meta-analysis was conducted for IMI at calving. The use of cephalosporins, cloxacillin, or penicillin with aminoglycoside significantly reduced the risk of new IMI at calving compared to non-treated controls (cephalosporins, RR = 0.37, 95% CI 0.23-0.65; cloxacillin, RR = 0.55, 95% CI 0.38-0.79; penicillin with aminoglycoside, RR = 0.42, 95% CI 0.26-0.72). Synthesis revealed challenges with a comparability of outcomes, replication of interventions, definitions of outcomes, and quality of reporting. The use of reporting guidelines, replication among interventions, and standardization of outcome definitions would increase the utility of primary research in this area.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.002 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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 teacher head, 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".