Adverse events with quetiapine and clarithromycin coprescription: A population‐based retrospective cohort study
Bibliographic record
Abstract
Background and Aims: Quetiapine is an atypical antipsychotic predominantly metabolized by the cytochrome P450 3A4 (CYP3A4) enzyme. We studied the risk of adverse events following coprescription of clarithromycin (a strong CYP3A4 inhibitor) versus azithromycin (not a CYP3A4 inhibitor) in quetiapine users. Materials and Methods: = 25,267). The primary outcome was the composite of hospital encounters with encephalopathy (defined as a diagnosis of delirium, disorientation, transient alteration of awareness, transient ischemic attack, or unspecified dementia), a fall, or a fracture within 30 days of new coprescription. Secondary outcomes were individual components of the composite outcome, hospital encounter with computed tomography (CT) head scan, and all-cause mortality. Results: Coprescription of clarithromycin versus azithromycin with quetiapine was associated with a higher risk of the primary composite outcome (365 of 16,909 clarithromycin users [2.2%] vs. 309 of 16,929 azithromycin users [1.8%]; absolute risk increase, 0.34% [95% confidence interval, CI, 0.04-0.63]; relative risk [RR], 1.19 [95% CI, 1.02-1.38]). This was primarily driven by an increase in fragility fractures (78 of 16,909 clarithromycin users [0.5%] vs. 45 of 16,923 azithromycin users [0.3%]; absolute risk increase, 0.20% [95% CI, 0.07-0.32]; RR, 1.74 [95% CI, 1.21-2.52]). Hospital encounters with a CT head scan were higher in clarithromycin users (220 of 16,909 [1.3%] vs. 175 of 16,923 azithromycin users [1.0%]; absolute risk increase, 0.27% [95% CI, 0.04-0.50]; RR, 1.26 [95% CI, 1.04-1.54]), but there was no difference in hospital encounters with encephalopathy, falls, or all-cause mortality between macrolide groups. Conclusion: Among adults taking quetiapine, concurrent use of clarithromycin compared with azithromycin was associated with a small but statistically greater 30-day risk of a hospital encounter for encephalopathy, falls, or fracture, which was predominantly related to a higher rate of fragility fractures.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".