Investigation of the use of meloxicam for reducing pain associated with castration and tail docking and improving performance in piglets
Bibliographic record
Abstract
Objectives: To determine the effect of meloxicam, administered to suckling piglets prior to castration and tail docking, on growth and mortality, and to determine evidence of pain reduction. Materials and methods: Piglets (n = 2888) were alternately assigned either to meloxicam (extra-label use) or a placebo injected intramuscularly 30 minutes prior to processing, which included tail docking for females, and tail docking and castration for males. All piglets were weighed on the day of processing (5 to 7 days of age) and at weaning (19 to 21 days of age). Vocalization scoring during castration, behavioral observations, and analysis of plasma cortisol concentrations were performed on a subset of animals. Results: Growth was not associated with treatment, but was positively correlated with weight at processing and negatively correlated with litter size. Mortality did not differ between treatment groups, but there was an interaction between treatment and parity, with piglets nursing older sows (parity > 5) and treated with placebo being 4.4 times more likely to die than piglets nursing older sows and treated with meloxicam (95% CI, 1.31-14.3) (P = .01). Behavior scores for isolation (isolating themselves from the other pigs) and plasma cortisol concentrations were higher for placebo-treated piglets than for meloxicam-treated piglets (P < .05). Implications: Routine treatment of piglets with meloxicam prior to castration and tail docking (extra-label use) does not improve growth, but may reduce mortality in litters nursing older sows. Observations of behavior and analysis of cortisol concentrations indicate meloxicam treatment does reduce pain.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 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".