Effects of a combination of umeclidinium/vilanterol on exercise endurance in patients with chronic obstructive pulmonary disease: two randomized, double-blind clinical trials
Bibliographic record
Abstract
OBJECTIVE: Exercise intolerance is a hallmark of chronic obstructive pulmonary disease (COPD). METHODS: Patients with COPD were randomized in two multicentre, double-blind, incomplete block crossover studies. Patients received two of six treatments in sequence (12 weeks each): placebo, umeclidinium (UMEC)/vilanterol (VI) (125/25 mcg or 62.5/25 mcg), VI (25 mcg) or UMEC (62.5 mcg or 125 mcg). Exercise endurance time (EET) and trough forced expiratory volume in 1 second (FEV1) (Week 12) were co-primary endpoints. Safety was monitored throughout. RESULTS: Both studies showed similar 3-hour post-dose EET improvements from baseline for UMEC/VI (Week 12). Significant EET improvements were observed with both UMEC/VI doses versus placebo at Week 12 in Study 418 (UMEC/VI 125/25 mcg: 65.8 s; p = 0.005; UMEC/VI 62.5/25 mcg: 69.4 s; p = 0.003), but not in Study 417, where a placebo effect was evident. Post hoc integrated data analysis showed significant but smaller EET improvements for both UMEC/VI doses versus placebo at Week 12 (UMEC/VI 125/25 mcg: 47.5 s; p = 0.002; UMEC/VI 62.5/25 mcg: 43.7 s; p = 0.001). Both studies showed trough FEV1 improvements at Week 12 for both UMEC/VI doses. The incidence of adverse events was similar between treatment groups within each study. CONCLUSIONS: UMEC/VI improved lung function and EET.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".