Fluoroquinolone use in a rural practice
Bibliographic record
Abstract
INTRODUCTION: Fluoroquinolones (FQs) are a commonly prescribed class of antibiotics in Canada. Evidence of a constellation of possible adverse events is developing. Central and peripheral nervous system abnormalities and collagen-related events (including aortic aneurysm/dissection, tendinopathy/rupture and retinal detachment) are associated with FQ exposure in large population-based aftermarket studies. In 2017, Health Canada warned about rare FQ-related persistent or disabling side effects. This study explores FQ use in a rural community. METHODS: Antibiotic prescriptions (including FQs) in the over 18 adult population (5416) were measured in the town of Sioux Lookout for 5 years, January 2013 to 31 December 2017. RESULTS: FQ prescriptions accounted for 16.0% of adult antibiotics, superseded by penicillins (21.1%) and macrolides (18.2%). Ciprofloxacin accounted for one half of FQ use (51.2%), followed by levofloxacin (36.7%) and norfloxacin (13.3%). FQs were commonly used for respiratory (33%) and urinary tract infections (18%). CONCLUSION: Aftermarket evidence reports increased risk of 'disabling and persistent serious adverse events'(Health Canada) in patients using FQs. Appropriate clinical caution should be exercised in the prescribing of FQs. Common overuse seems to occur in the treatment of uncomplicated community-acquired pneumonia and cystitis, despite recommendations to use other antimicrobial agents as first-line treatments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.005 | 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".