<p>Comparative Effectiveness Of Fluoroquinolone Antibiotic Use In Uncomplicated Acute Exacerbations Of COPD: A Multi-Cohort Study</p>
Bibliographic record
Abstract
Purpose: Fluoroquinolone antibiotics are associated with rare, but severe adverse events. They are frequently used for the treatment of acute exacerbations of COPD (AECOPD). While their effectiveness in severe exacerbations requiring hospitalisation has been well documented, the potential benefit in the ambulatory setting is less clear, especially in uncomplicated patients with COPD. Patients and characteristics: We carried out a retrospective cohort study using health care databases from six Canadian provinces in subjects visiting their physician for uncomplicated COPD. Subjects dispensed either a quinolone or other antibiotics were compared using inverse probability of treatment weights with high dimensional propensity scores on 30-day outcomes, including repeat visits, hospitalisation for AECOPD and subsequent antibiotic prescription. Results from each province were combined by random effects meta-analysis. Results: We identified 286,866 AECOPD events among 203,642 unique individuals. The frequency of fluoroquinolone use, mostly levofloxacin and moxifloxacin, varied by province and ranged from 8% to 32% of AECOPD antibiotic prescriptions. The risk of a repeat ambulatory care visit was increased among patients who were dispensed a fluoroquinolone compared with other antibiotics (OR 1.32, 95% CI 1.27-1.36). The risk of a hospitalisation for AECOPD was also higher with fluoroquinolones (OR 1.52, 95% CI 1.33-1.74). There was no difference in subsequent antibiotic prescriptions (OR 1.00, 95% CI 0.94-1.07). Conclusion: There is no apparent benefit in short-term outcomes with fluoroquinolones as compared to other antibiotics for the ambulatory treatment of AECOPD in uncomplicated patients. These findings support current recommendations that fluoroquinolones be reserved for AECOPD in patients with recurrent exacerbations, significant co-morbidity or requiring hospitalisation.
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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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.015 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".