Short-acting β <sub>2</sub> -agonist use, exacerbation risk and triple therapy in COPD: <i>post hoc</i> analyses of ETHOS
Bibliographic record
Abstract
Background Short-acting β 2 -agonist (SABA) rescue therapy can relieve COPD symptoms. We assessed post-randomisation treatment effects on exacerbations and health-related quality of life in ETHOS by rescue SABA use. Methods In ETHOS ( NCT02465567 ), symptomatic people with COPD and an exacerbation history were randomly assigned 1:1:1:1 to budesonide/glycopyrronium/formoterol fumarate dihydrate (BGF) (320/14.4/10 or 160/14.4/10 μg), glycopyrronium/formoterol fumarate dihydrate (GFF) (14.4/10 μg) or budesonide/formoterol fumarate dihydrate (BFF) (320/10 μg). Post hoc analyses assessed exacerbation rates by baseline and post-randomisation SABA use (>4 versus ≤4 inhalations·day −1 ), St George's Respiratory Questionnaire change from baseline by post-randomisation SABA use (>4 versus ≤4 inhalations·day −1 ), and post-randomisation SABA use surrounding (30 days before, day of onset, 30 days after) the first exacerbation. Results Across treatments, higher moderate/severe exacerbation rates were observed for participants with higher (range: 1.62–2.51) versus lower (range: 1.14–1.51) SABA use at baseline or post-randomisation. Post-randomisation SABA use increased in the 30 days preceding, and decreased in the 30 days following, an exacerbation. Evidence of BGF benefit versus dual therapies in reducing moderate/severe exacerbation rates were seen regardless of SABA use level at baseline or post-randomisation, with greater BGF benefit observed versus GFF with higher SABA use (rate ratios (95% CI): high baseline SABA, 0.62 (0.53–0.72); high post-randomisation SABA, 0.64 (0.54–0.76)). Conclusion These results suggest increased SABA use is associated with an impending exacerbation. Further, BGF reduces exacerbation rates regardless of SABA use, with greater benefit in those with higher SABA use.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".