Efficacy of dexamethasone, salbutamol, and reduced respirable particulate concentration on aerobic capacity in horses with smoke-induced mild asthma
Bibliographic record
Abstract
Abstract Background Mild asthma in horses decreases racing performance and impairs gas exchange. The efficacy of treatment on performance is unknown. Hypothesis Treatment targeting lung inflammation improves V˙O2peak in horses with mild asthma. Animals Thoroughbred polo horses (n = 12) with smoke-induced mild asthma. Horses were exposed to increased ambient particulate matter (35.51 μg/m3 [PM2.5]; day mean, centrally measured) from day −33 to 0, from bushfire smoke (natural model). Methods Prospective, randomized, placebo-controlled, double-blinded clinical trial. All horses completed 3 V˙O2peak tests, measuring aerobic and anaerobic variables: day 0 -baseline; day 16 -after dexamethasone (20 mg IM q24h; DEX, n = 6) or saline treatment (SALINE, n = 6), under improved ambient PM2.5 concentrations (7.04 μg/m3); day 17-15-30mins after inhaled salbutamol (1500 μg). Bronchoalveolar lavage and mucus scoring were performed on day −8 and day 20. Linear mixed effects models were used to examine the effects of timepoint and treatment group on BAL differential cell counts, mucus scores, aerobic and anaerobic variables. Results Horses’ mucus scores improved significantly from day −8 to 20 by 1.27 ± .38 (P = .01). There was a significant increase in V˙O2peak of 15.5 ± 4.0 mL(min.kg)−1 from day 0 to 17 (P = .002), representing an average (mean) increase in V˙O2peak of 13.2%. There was no difference in V˙O2peak between treatment groups (SALINE versus DEX) at any timepoint. Conclusions and Clinical Importance This study highlighted the key role of improved air quality on functionally important airway inflammation. Evidence provided is central to increasing owner compliance regarding improved air quality for the treatment and prevention of mild asthma.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".