SIMILAR EFFICACY FOLLOWING FOUR WEEKS TREATMENT OF ASTHMATICS WITH FORMOTEROL 12 μG B.D. DELIVERED BY TWO DIFFERENT DRY POWDER INHALERS: DIFFERENCES IN INHALER HANDLING
Bibliographic record
Abstract
SUMMARY This randomised, multicentre, parallel‐group study compared the clinical efficacy and ease of handling of two dry powder inhalers delivering the long‐acting β2‐agonist formoterol. After run‐in, 200 asthmatics on treatment with inhaled corticosteroids and still presenting with suboptimal asthma control were randomised to receive 12 μg formoterol twice daily via either the Aerolizer inhaler (Foradil® Aerolizer™) or the Turbuhaler inhaler (Oxis® Turbuhaler®) for four weeks. Study variables included the mean morning pre‐medication peak expiratory flow (PEF) during the last seven days of treatment and the correct inhaler handling according to inhaler‐specific checklists. The mean difference in the effect on morning pre‐medication PEF was 13.86 l/min in favour of formoterol via the Aerolizer inhaler (90% confidence interval 2.50, 25.21) in the intent‐to‐treat population. Eighty‐six per cent of the patients under treatment with formoterol via the Turbuhaler inhaler performed correctly all the essential inhalation manoeuvres, whereas 98% of those on the Aerolizer inhaler did so. These results strongly suggest similar clinical efficacy with twice daily treatment of formoterol 12 μg metered dose delivered either by the Aerolizer, or the Turbuhaler device. They also suggest that handling the Aerolizer is easier than that of the Turbuhaler.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".