Effects of azithromycin on bronchial remodeling in the natural model of severe neutrophilic asthma in horses
Bibliographic record
Abstract
Steroid resistance in asthma has been associated with neutrophilic inflammation and severe manifestations of the disease. Macrolide add-on therapy can improve the quality of life and the exacerbation rate in refractory cases, possibly with greater effectiveness in neutrophilic phenotypes. The mechanisms leading to these beneficial effects are incompletely understood and whether macrolides potentiate the modulation of bronchial remodeling induced by inhaled corticosteroids (ICS) is unknown. The objective of this study was to determine if adding azithromycin to ICS leads to further improvement of lung function, airway inflammation and bronchial remodeling in severe asthma. The combination of azithromycin (10 mg/kg q48h PO) and inhaled fluticasone (2500 µg q12h) was compared to the sole administration of fluticasone for five months in a randomized blind trial where the lung function, airway inflammation and bronchial remodeling (histomorphometry of central and peripheral airways and endobronchial ultrasound) of horses with severe neutrophilic asthma were assessed. Although the proportional reduction of airway neutrophilia was significantly larger in the group receiving azithromycin, the lung function and the peripheral and central airway smooth muscle mass decreased similarly in both groups. Despite a better control of airway neutrophilia, azithromycin did not potentiate the other clinical effects of fluticasone.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".