Stable COPD: predicting benefit from high-dose inhaled corticosteroid treatment
Bibliographic record
Abstract
The role of inhaled corticosteroids in the management of chronic obstructive pulmonary disease (COPD) remains controversial. The purpose of this study was to evaluate whether sputum eosinophilia (defined as eosinophils > or = 3%) predicts clinical benefit from inhaled corticosteroid treatment in patients with smoking-related clinically stable moderate-to-severe COPD. Forty consecutive patients with effort dyspnoea (mean age 67 yrs; 52 pack-yr smoking history; post-bronchodilator forced expiratory volume in one second (FEV1) <60% predicted, consistent with moderate-to-severe smoking-related chronic airflow limitation) were enrolled. Subjects were treated with inhaled placebo followed by inhaled budesonide (Pulmicort Turbuhaler 1,600 microg.day(-1)), each given for 4 weeks. While the treatment was single-blind (subject level), sputum cell counts before and after treatment interventions were double-blind, thus removing bias. Outcome variables included spirometry, quality-of-life assessment and 6-min walk test. Sputum eosinophilia was present in 38% of subjects. In these, budesonide treatment normalised the eosinophil counts and, in comparison to placebo treatment, resulted in clinically significant improvement in the dyspnoea domain of the disease-specific chronic respiratory questionnaire (0.8 versus 0.3) and a small but statistically significant improvement in post-bronchodilator spirometry (FEV1 100 mL versus 0 mL; p<0.05). In conclusion, sputum eosinophilia predicts short-term clinical benefit from high-dose inhaled corticosteroid treatment in patients with stable moderate-to-severe chronic obstructive pulmonary disease.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".