Prospective evaluation of the efficacy of inhaled steroids administered via the AeroDawg spacing chamber in management of dogs with chronic cough
Bibliographic record
Abstract
BACKGROUND: Glucocorticoids are frequently required for management of cough because of inflammatory airway disease (IAD) and airway collapse (AWC). OBJECTIVES/HYPOTHESIS: To determine the efficacy and feasibility of inhaled administration of corticosteroids in controlling cough in dogs with noninfectious airway disease. ANIMALS: Thirty-six client-owned dogs. METHODS: Dogs were prospectively recruited for this placebo-controlled cross-over study. Inflammatory airway disease was diagnosed through bronchoalveolar lavage cytology. Airway collapse was diagnosed through bronchoscopy, or if dogs were unsuitable anesthetic candidates, by crackles on auscultation, radiographic changes in airway diameter, or fluoroscopy. Dogs were randomly assigned to receive placebo or fluticasone propionate for the first 2 weeks of the trial then crossed over to fluticasone. A quality of life (QOL) survey (best score 0, worst score 85) was completed at 0 and 6 weeks. A visual-analog cough survey was submitted at 0, 2, 4, and 6 weeks to assess cough, feasibility, and adverse effects of treatment. RESULTS: For 32 dogs, QOL score at study end (mean 11.3 ± 9.7) was significantly lower (P < .0001) compared to entry (mean 28.1 ± 14.1), with a median change of 69% in QOL score, indicating improved quality of life. Cough frequency, duration, and severity were significantly (P < .0001) decreased at study end. Feasibility of aerosolized delivery improved with continued use (P = .05) with only 1 dog unable to accept inhaled medication. CONCLUSION AND CLINICAL IMPORTANCE: This study supports the utility of fluticasone propionate by inhalation in management of cough in dogs with IAD and AWC.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| 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".