Use of antidepressant serotoninergic medications and cardiac valvulopathy: a nested case–control study in the health improvement network (THIN) database
Bibliographic record
Abstract
WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT • Some medications can induce cardiac valvulopathy by acting on 5‐HT2B receptors. • Antidepressant serotoninergic medications may activate 5‐HT2B receptors via a direct or an indirect mechanism. WHAT THIS STUDY ADDS • These data do not appear to support an association between exposure to antidepressant serotoninergic medications and an increased risk of cardiac valvulopathy. AIMS To quantify the risk of cardiac valvulopathy (CV) associated with the use of antidepressant serotoninergic medications (SMs). METHODS We conducted a case–control study nested in a cohort of users of antidepressant SMs selected from The Health Improvement Network database. Patients who experienced a CV event during follow‐up were cases. Cases were ascertained in a random sample of them. Up to 10 controls were matched to each case by sex, age, month and year of the study entry. Use of antidepressant SMs during follow‐up was defined as current (the last prescription for antidepressant SMs occurred in the 2 months before the CV event), recent (in the 2–12 months before the CV event) and past (>12 months before the CV event). We fitted a conditional regression model to estimate the association between use of antidepressant SMs and the risk of CV by means of odds ratios (ORs) and corresponding 95% confidence intervals (CIs). Sensitivity analyses were conducted to test the robustness of our results. RESULTS The study cohort included 752 945 subjects aged 18–89 years. Throughout follow‐up, 1663 cases (incidence rate: 3.4 per 10 000 person‐years) of CV were detected and were matched to 16 566 controls. The adjusted OR (95% CI) for current and recent users compared with past users of antidepressant SMs were 1.16 (0.96–1.40) and 1.06 (0.93–1.22), respectively. Consistent effect estimates were obtained when considering cumulative exposure to antidepressant SMs during follow‐up. CONCLUSIONS These results would suggest that exposure to antidepressant SMs is not associated with an increased risk of CV.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| 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".