Fluoroquinolones and the risk of severe hypoglycaemia among sulphonylurea users: Population‐based cohort study
Bibliographic record
Abstract
AIM: Fluoroquinolone-related hypoglycaemia is rare but may become clinically relevant in individuals at high baseline hypoglycaemic risk, such as patients with diabetes using sulphonylureas. Our population-based cohort study assessed whether fluoroquinolones are associated with an increased risk of severe hypoglycaemia compared with amoxicillin among patients treated with sulphonylureas. MATERIALS AND METHODS: Using the UK's Clinical Practice Research Datalink Aurum linked to hospitalization and vital statistics data, we assembled a base cohort of patients who initiated second-generation sulphonylureas (1998-2020). The study cohort included patients initiating either fluoroquinolones or amoxicillin while on sulphonylureas. Using an intent-to-treat exposure definition, we assessed the 30-day risk of severe hypoglycaemia (hospitalization with or death because of hypoglycaemia) associated with fluoroquinolones compared with amoxicillin. Cox models estimated hazard ratios (HRs) with 95% confidence intervals (CIs) of severe hypoglycaemia after 1:5 matching on previous sulphonylurea use and propensity scores. Secondary analyses were stratified by demographics and glycated haemoglobin. RESULTS: Overall, 143 417 patients initiated fluoroquinolones (n = 13 123) or amoxicillin (n = 130 294) while on sulphonylureas. Compared with amoxicillin, fluoroquinolones were not associated with the risk of severe hypoglycaemia (HR, 1.17; 95% CI, 0.91-1.50). Fluoroquinolones were associated with an increased risk in patients <65 years (HR, 2.90; 95% CI, 1.41-5.97) but not in those ≥65 years (HR, 1.03; 95% CI, 0.79-1.35) in stratified analyses. There was no evidence of effect modification by sex or glycated haemoglobin. CONCLUSIONS: In patients using second-generation sulphonylureas, fluoroquinolones were not associated with an increased risk of severe hypoglycaemia compared with amoxicillin. An increased risk among younger adults is possible.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".