Concomitant Use of Selective Serotonin Reuptake Inhibitors and Oral Anticoagulants and Risk of Major Bleeding: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
BACKGROUND: Selective serotonin reuptake inhibitors (SSRIs), the most prescribed antidepressants, are associated with a modestly increased risk of major bleeding. However, in patients treated with both SSRIs and oral anticoagulants (OACs), the risk of major bleeding may be substantial. OBJECTIVE: To assess the risk of major bleeding associated with concomitant use of SSRIs and OACs, compared with OAC use alone. METHODS: We searched MEDLINE, Embase, PsycINFO, and the Cochrane Central Register of Controlled Trials (from inception to December 1, 2021) for clinical trials and observational studies assessing the association between concomitant use of SSRIs and OACs and the risk of major bleeding. Given sufficient homogeneity of studies, we conducted a random-effects meta-analysis to estimate a pooled hazard ratio (HR) of major bleeding associated with concomitant use of SSRIs and OACs, compared with OAC use alone. RESULTS: The review comprised 14 studies, including 7 cohort and 7 nested case-control studies. Following assessment of clinical and methodological heterogeneity, eight studies with a total of 98,070 patients were eligible for the meta-analysis. The pooled HR of major bleeding associated with concomitant use of SSRIs and OACs was 1.35 (95% confidence interval [CI]: 1.14-1.58). In secondary analyses, the pooled HR for concomitant use of SSRIs and direct OACs was 1.47 (95% CI: 1.03-2.10). CONCLUSION: Concomitant use of SSRIs and OACs was associated with an increased risk of major bleeding. Overall, our findings suggest that physicians may need to tailor treatment according to individual patient risk factors for bleeding when prescribing SSRIs to patients using OACs.
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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 | 0.013 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.042 |
| Bibliometrics | 0.008 | 0.009 |
| 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) | 0.004 | 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".