Risk of Ventricular Arrhythmia with Citalopram and Escitalopram: A Population-Based Study
Bibliographic record
Abstract
BACKGROUND: The risk of ventricular arrhythmia with citalopram and escitalopram is controversial. In this study we investigated the association between these two drugs and the risk of ventricular arrhythmia. METHODS: We conducted a population-based retrospective cohort study of older adults (mean age 76 years) from 2002 to 2012 in Ontario, Canada, newly prescribed citalopram (n = 137 701) or escitalopram (n = 38 436), compared to those prescribed referent antidepressants sertraline or paroxetine (n = 96 620). After inverse probability of treatment weighting using a propensity score, the baseline characteristics of the comparison groups were similar. The primary outcome was a hospital encounter with ventricular arrhythmia within 90 days of a new prescription, assessed using hospital diagnostic codes. The secondary outcome was all-cause mortality within 90 days. RESULTS: Citalopram was associated with a higher risk of a hospital encounter with ventricular arrhythmia compared with referent antidepressants (0.06% vs. 0.04%, relative risk [RR] 1.53, 95% confidence intervals [CI]1.03 to 2.29), and a higher risk of mortality (3.49% vs. 3.12%, RR 1.12, 95% CI 1.06 to 1.18). Escitalopram was not associated with a higher risk of ventricular arrhythmia compared with the referent antidepressants (0.03% vs. 0.04%, RR 0.84, 95% CI 0.42 to 1.68), but was associated with a higher risk of mortality (2.86% vs. 2.63%, RR 1.09, 95% CI 1.01 to 1.18). CONCLUSION: Among older adults, initiation of citalopram compared to two referent antidepressants was associated with a small but statistically significant increase in the 90-day risk of a hospital encounter for ventricular arrhythmia.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".