Effects of soaked hay on lung function and airway inflammation in horses with severe asthma
Bibliographic record
Abstract
Abstract Background Reducing inhaled dust particles improves lung function in horses with severe asthma. Soaked hay is commonly used by owners, but its efficacy in improving lung function and inflammation has not been documented. Objectives To measure the effects of soaked hay and alfalfa pellets in horses with severe asthma. Animals Ten adult horses with severe asthma from a research colony. Methods Prospective controlled trial. Horses in clinical exacerbation were housed indoors and allocated to be fed either soaked hay (n = 5) or alfalfa pellets (n = 5) for 6 weeks. Soaked hay was immersed for 45 minutes and dried out hay was discarded between meals. Pulmonary function and clinical scores were measured before and after 2, 4, and 6 weeks. Tracheal mucus scores and bronchoalveolar lavages were performed before and after 6 weeks. Lung function was analyzed with a linear mixed model using log-transformed data. Results Lung resistance decreased from (median (range)) 2.47 (1.54-3.95) to 1.59 (0.52-2.10) cmH2O/L/s in the pellets group and from 1.89 (1.2-3.54) to 0.61 (0.42-2.08) cmH2O/L/s in the soaked hay group over the 6-week period for an average difference of 1.06 cmH2O/L/s for pellets (95% confidence interval [95% CI]: 0.09-2.04, P = .03, not significant after correction) and 1.31 cmH2O/L/s for soaked hay (95% CI: −0.23 to 2.85, P < .001, significant). Conclusion and Clinical Importance Soaked hay can control airway obstruction in horses with severe asthma. The strict protocol for soaking and discarding dried-out hay in this study could however be considered too great of an inconvenience by owners.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".