Inhaled corticosteroids and mortality in chronic obstructive pulmonary disease
Bibliographic record
Abstract
BACKGROUND: Clinical studies suggest that inhaled corticosteroids reduce exacerbations and improve health status in chronic obstructive pulmonary disease (COPD). However, their effect on mortality is unknown. METHODS: A pooled analysis, based on intention to treat, of individual patient data from seven randomised trials (involving 5085 patients) was performed in which the effects of inhaled corticosteroids and placebo were compared over at least 12 months in patients with stable COPD. The end point was all-cause mortality. RESULTS: Overall, 4% of the participants died during a mean follow up period of 26 months. Inhaled corticosteroids reduced all-cause mortality by about 25% relative to placebo. Stratification by individual trials and adjustments for age, sex, baseline post-bronchodilator percentage predicted forced expiratory volume in 1 second, smoking status, and body mass index did not materially change the results (adjusted hazard ratio (HR) 0.73; 95% confidence interval (CI) 0.55 to 0.96). Although there was considerable overlap between subgroups in terms of effect sizes, the beneficial effect was especially noticeable in women (adjusted HR 0.46; 95% CI 0.24 to 0.91) and former smokers (adjusted HR 0.60; 95% CI 0.39 to 0.93). CONCLUSIONS: Inhaled corticosteroids reduce all-cause mortality in COPD. Further studies are required to determine whether the survival benefits persist beyond 2-3 years.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".