Adverse Cardiovascular Events in Antidepressant Trials Involving High-Risk Patients: A Systematic Review of Randomized Trials
Bibliographic record
Abstract
OBJECTIVE: To examine whether selective serotonin reuptake inhibitor (SSRI) antidepressants were associated with an increased or decreased risk of cardiovascular adverse events (AEs). METHODS: We conducted a systematic review of randomized controlled trials published between 1967 and May 2005 that treated patients with cardiac disease, diabetes mellitus, stroke, geriatric age, nicotine dependence, alcoholism, HIV infection, and obesity. We defined serious AEs as death due to a cardiovascular cause, heart failure, stroke, transient ischemic attack, and myocardial infarction. Nonserious AEs were defined as palpitations, chest pain, angina, arrhythmia, hypertension, hypotension-syncope, and unspecified cardiovascular or neurologic events. Adverse event rates were calculated in 4 groups: SSRIs, tricyclic antidepressants (TCAs), other active therapies, and placebo. RESULTS: Stroke and cardiac patients were the highest-risk groups for cardiovascular AEs. We were unable to detect differences in odds between SSRI and placebo for both serious (odds ratio [OR] 0.69; 95% confidence interval [CI], 0.39 to 1.21) and nonserious (OR 1.18; 95% CI, 0.90 to 1.57) cardiovascular AEs. There was a significant decrease in the odds of nonserious cardiovascular AEs (OR 0.46; 95% CI, 0.24 to 0.86, P = 0.02) for patients receiving SSRIs, compared with TCAs. Over one-half of the selected trials did not report the presence or absence of cardiovascular events. CONCLUSIONS: This systematic review of antidepressant trials in high-risk patients did not determine whether SSRIs are associated with a greater or lesser risk of cardiovascular AEs. Reasons for this conclusion include the rarity of serious AEs, the lack of large trials in these patients, and a lack of adequate reporting of AEs in published trials. Further trials assessing the risk of cardiovascular AEs and better trial reporting are needed.
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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 | 0.030 | 0.111 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.013 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".