A systematic review and network meta-analysis of injectable antibiotic options for the control of bovine respiratory disease in the first 45 days post arrival at the feedlot
Bibliographic record
Abstract
We conducted a systematic review and network meta-analysis to determine the comparative efficacy of antibiotics used to control bovine respiratory disease (BRD) in beef cattle on feedlots. The information sources for the review were: MEDLINE®, MEDLINE In-Process and MEDLINE® Daily, AGRICOLA, Epub Ahead of Print, Cambridge Agricultural and Biological Index, Science Citation Index, Conference Proceedings Citation Index - Science, the Proceedings of the American Association of Bovine Practitioners, World Buiatrics Conference, and the United States Food and Drug Administration Freedom of Information New Animal Drug Applications summaries. The eligible population was weaned beef cattle raised in intensive systems. The interventions of interest were injectable antibiotics used at the time the cattle arrived at the feedlot. The outcome of interest was the diagnosis of BRD within 45 days of arrival at the feedlot. The network meta-analysis included data from 46 studies and 167 study arms identified in the review. The results suggest that macrolides are the most effective antibiotics for the reduction of BRD incidence. Injectable oxytetracycline effectively controlled BRD compared with no antibiotics; however, it was less effective than macrolide treatment. Because oxytetracycline is already commonly used to prevent, control, and treat BRD in groups of feedlot cattle, the use of injectable oxytetracycline for BRD control might have advantages from an antibiotic stewardship perspective.
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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 | 0.016 | 0.048 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.029 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".