Environmental heat and airborne pollen concentration are associated with increased asthma severity in horses
Bibliographic record
Abstract
REASON FOR PERFORMING STUDY: Clinical exacerbations of severe equine asthma (formerly recurrent airway obstruction [RAO]) are more frequently reported during winter when horses are exposed to airborne dusts during stabling. However, we have also observed a worsening of clinical signs on days during a heatwave. OBJECTIVES: To investigate the association between environmental temperature and humidity and clinical signs of asthma in horses during clinical exacerbation of the disease. STUDY DESIGN: Retrospective longitudinal study. METHODS: Historical data on 14 severe asthmatic horses exposed to a dusty environment and evaluated using a previously validated clinical scoring system were analysed. Barn temperature and relative humidity values were obtained and air enthalpy (h) calculated. Correlation tests were used to study the relationship between mean daily clinical scores of horses and environmental variables. Lung function parameters recorded at 4 day intervals during hot (25°C) and warm (18°C) barn conditions were compared using a paired t test. RESULTS: Significant positive correlations were observed between the mean daily clinical score and temperature (r = 0.58, P = 0.01) and air enthalpy (r = 0.55, P = 0.02). Maximal daily temperature correlated with airborne pollen concentrations (r = 0.51, P = 0.0002). In the absence of changes in the management of horses, higher barn temperature and enthalpy were associated with increased transpulmonary pressure (P = 0.005), pulmonary resistance (P = 0.008) and elastance values (P = 0.005). CONCLUSIONS: Providing a cold environment may help attenuate the severity of airway obstruction in uncontrolled exacerbations of severe equine asthma. Furthermore, variations in environmental heat and associated pollen concentrations should also be taken into account when evaluating the response to therapy in clinical or research settings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".