A randomised, double-blind, four-way, crossover trial comparing the 24-h FEV1 profile for once-daily versus twice-daily treatment with olodaterol, a novel long-acting β2-agonist, in patients with chronic obstructive pulmonary disease
Bibliographic record
Abstract
BACKGROUND: This randomised, double-blind, four-way, crossover, Phase II study compared the 24-h forced expiratory volume in 1 s (FEV1) profile of alternative dosing frequencies of two total daily doses of olodaterol (5 and 10 μg) in patients with chronic obstructive pulmonary disease (COPD). METHODS: Patients received olodaterol 2 μg twice daily (BID), 5 μg BID, 5 μg once daily (QD) and 10 μg QD in a randomised sequence over 3-week treatment periods. Co-primary end points were FEV1 area under the curve from 0 to 12 h (AUC0-12) and area under the curve from 12 to 24 h (AUC12-24) responses. Additional lung-function responses, pharmacokinetics and safety were assessed. RESULTS: 47 patients were treated. All olodaterol doses provided significant increases in FEV1 versus baseline (p < 0.001) and FEV1 time profiles were nearly identical for olodaterol 5 and 10 μg QD. Olodaterol 5 μg QD demonstrated improved FEV1 AUC0-12 and similar AUC12-24 versus 2 μg BID. Olodaterol 5 μg QD showed slightly increased FEV1 AUC0-12 but lower AUC12-24 compared to 5 μg BID. Bronchodilation over 24 h was similar for olodaterol 5 μg QD and BID. All doses were well tolerated. CONCLUSIONS: Olodaterol 5 μg QD is efficacious in COPD, with a superior bronchodilatory profile compared to 2 μg BID, which is close to the same total daily dose, and a similar degree of bronchodilation over 24 h compared with double the daily dose (administered as 10 μg QD or 5 μg BID). TRIAL REGISTRATION: ClinicalTrials.gov: NCT00846768.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".