Antidepressants, metoprolol and the risk of bradycardia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Case reports and pharmacologic theory suggest that some antidepressants can interfere with the hepatic metabolism of metoprolol by cytochrome P450 2D6 (CYP2D6), potentially increasing the risk of bradycardia. The objective of this study was to characterize the clinical consequences of this potential drug interaction at the population level. We conducted a population-based, nested case-control study of Ontario residents 66 years of age or older receiving metoprolol. Cases hospitalized for bradycardia were compared with matched controls (4:1) to explore the odds ratio for initiation of antidepressants that inhibit CYP2D6 (fluoxetine and paroxetine) and those that do not inhibit CYP2D6 (fluvoxamine, citalopram, venlafaxine, and sertraline) 30 days before hospitalization. From April 1997 to March 2009, we identified 332,254 older patients continuously receiving metoprolol, of whom 8232 (2.5%) were treated in hospital for bradycardia. The adjusted odds ratio for exposure to fluoxetine or paroxetine compared with other antidepressants 30 days prior to hospitalization for bradycardia was 0.76 (95% confidence interval 0.42-1.37). Among older patients receiving metoprolol, the initiation of antidepressants that inhibit CYP2D6 was not associated with a significant increase in the risk of bradycardia compared with antidepressants that do not inhibit CYP2D6.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it