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.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.008 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".