Incidence of intramammary infections during the dry period without or with antibiotic treatment in dairy cows – a quantitative analysis of published data
Bibliographic record
Abstract
The study was aimed at summarising the literature that compares the incidence levels of spontaneously occurring intramammary infections (IMI) during the dry period, without versus with antibiotic dry cow treatment (DCT). A meta-analytic relative risk (RR) calculation was implemented when a priori relevant. Two main categories of comparison were used in the 36 selected papers. In the first category, the udder quarters were randomly allocated (at quarter or cow level) to an untreated or a treated group. Quarter incidence averaged 12.8% (weighted mean) in untreated quarters, and depending on the DCT used, from 6.6 to 8.0% in treated quarters. The meta-analytic RR of new IMI for untreated versus treated quarters varied from 1.54 to 1.94, depending on the DCT used. DCT was mainly found effective against IMI due to streptococci and coagulase-positive staphylococci. Based on only a few papers, the application of an internal teat sealer was associated to a quite similar (or possibly better) protection against IMI than DCT, but only in a subpopulation of particular (selected) cows. In the second category of studies, a selective dry cow or quarter antibiotic-treatment (selective DCT or DQT), according to cow or quarter selection criteria, was compared to blanket DCT. The meta-analytic RR of new IMI was 1.71 for selective DCT versus blanket DCT. Selective DQT seemed to be more at risk than selective DCT, but consisted of treating a much lower proportion of quarters. The summary-results provided by our meta-analysis should only be used with caution, due to possibly low external validity. More research seems to be relevant on the risk factors of new IMI during the dry period to make the outcomes of omission of DCT in selected cows more predictable under field conditions.
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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 | 0.023 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.032 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".