A novel study design for antibiotic trials in acute exacerbations of COPD: MAESTRAL methodology
Bibliographic record
Abstract
Antibiotics, along with oral corticosteroids, are standard treatments for acute exacerbations of chronic obstructive pulmonary disease (AECOPD). The ultimate aims of treatment are to minimize the impact of the current exacerbation, and by ensuring complete resolution, reduce the risk of relapse. In the absence of superiority studies of antibiotics in AECOPD, evidence of the relative efficacy of different drugs is lacking, and so it is difficult for physicians to select the most effective antibiotic. This paper describes the protocol and rationale for MAESTRAL (moxifloxacin in AECBs [acute exacerbation of chronic bronchitis] trial; www.clinicaltrials.gov: NCT00656747), one of the first antibiotic comparator trials designed to show superiority of one antibiotic over another in AECOPD. It is a prospective, multinational, multicenter, randomized, double-blind controlled study of moxifloxacin (400 mg PO [per os] once daily for 5 days) vs. amoxicillin/clavulanic acid (875/125 mg PO twice daily for 7 days) in outpatients with COPD and chronic bronchitis suffering from an exacerbation. MAESTRAL uses an innovative primary endpoint of clinical failure: the requirement for additional or alternate treatment for the exacerbation at 8 weeks after the end of antibiotic therapy, powered for superiority. Patients enrolled are those at high-risk of treatment failure, and all are experiencing an Anthonisen type I exacerbation. Patients are stratified according to oral corticosteroid use to control their effect across antibiotic treatment arms. Secondary endpoints include quality of life, symptom assessments and health care resource 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 | 0.152 | 0.276 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.038 | 0.005 |
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".