TNFα antagonists for acute exacerbations of COPD: a randomised double-blind controlled trial
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: The purpose of this randomised double-blind double-dummy placebo-controlled trial was to investigate whether etanercept, a tumour necrosis factor α (TNFα) antagonist, would provide more effective anti-inflammatory treatment for acute exacerbations of chronic obstructive pulmonary disease (COPD) than prednisone. METHODS: We enrolled 81 patients with acute exacerbations of COPD and randomly assigned them to treatment with either 40 mg oral prednisone given daily for 10 days or to 50 mg etanercept given subcutaneously at randomisation and 1 week later. Both groups received levofloxacin for 10 days plus inhaled bronchodilators. The primary endpoint was the change in the patient's forced expiratory volume in 1 s (FEV(1)) 14 days after randomisation. Secondary endpoints included 90-day treatment failure rates and dyspnoea and quality of life. RESULTS: At 14 days the mean±SE change in FEV(1) from baseline was 20.1±5.0% and 15.2±5.7% for the prednisone and etanercept groups, respectively. The mean between-treatment difference was 4.9% (95% CI -10.3% to 20.2%), p=0.52. Rates of treatment failure at 90 days were similar in the prednisone and etanercept groups (32% vs 40%, p=0.44), as were measures of dyspnoea and quality of life. Subgroup analysis revealed that patients with serum eosinophils >2% at exacerbation tended to experience fewer treatment failures if treated with prednisone compared with etanercept (22% vs 50%, p=0.08). CONCLUSIONS: Etanercept was not more effective than prednisone for treatment of acute exacerbations of COPD. Efficacy of prednisone was most apparent in patients who presented with serum eosinophils >2%. CLINICAL TRIALS: gov number NCT 00789997.
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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 | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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 it