Dose-related efficacy of GSK573719, a new long-acting muscarinic receptor antagonist (LAMA) offering sustained 24-hour bronchodilation, in COPD
Bibliographic record
Abstract
Introduction: GSK573719 is an inhaled LAMA with sustained 24-hour activity under development as a once-daily therapy for COPD. Objective: To evaluate the dose response of GSK573719 in patients with COPD. Methods: This was a multicentre, randomised, double-blind, placebo-controlled, parallel-group study evaluating GSK573719 administered once daily via a novel single-step activation dry powder inhaler in patients with COPD (FEV 1 of ≥35 and ≤70% predicted). The primary endpoint was morning pre-dose (trough) FEV 1 after 28 days of treatment. Results: All doses of GSK573719 significantly increased trough FEV 1 compared with placebo, with improvement ranging from 150 to 168mL (p<0.001). All doses significantly increased 0–6 hour weighted mean FEV 1 compared with placebo with differences ranging from 113 to 211mL (p<0.001). Additionally, all doses demonstrated significant improvements over placebo in serial FEV 1 at each measured time point over 24 hours (p≤0.038). Reductions in albuterol use and improvements in FVC were also noted for all doses. All doses were well tolerated. Conclusion: Once-daily dosing with GSK573719 provides clinically significant and sustained improvement in lung function and is well tolerated over 24 hours in patients with COPD. Funded by GSK (AC4113589; NCT01030965 )
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".