Selective Serotonin Reuptake Inhibitors Are Associated With a Modest Increase in the Risk of Upper Gastrointestinal Bleeding
Bibliographic record
Abstract
OBJECTIVES: The use of the common antidepressant class of serotonin-specific reuptake inhibitors (SSRIs) is associated with an increased risk of upper gastrointestinal bleeding (UGIB). Proton pump inhibitors (PPIs) have been demonstrated to reduce the risk of gastrointestinal bleeding secondary to other risk factors, most notably non-steroidal anti-inflammatory drug (NSAID) use. The role for PPIs in chronic SSRI users without other risk factors remains uncharacterized. METHODS: We used the Manitoba Population Health Research Data Repository to perform a population-based matched case-control analysis. All patients admitted to the hospital with a primary diagnosis of UGIB were matched to non-bleeding controls. We used conditional regression analysis to determine the risk of UGIB associated with SSRI use, and the risk reduction associated with concomitant PPI use, both for users and non-users of NSAIDs. RESULTS: SSRI use was associated with a modest increase in the risk of UGIB (odds ratio (OR), 1.43; 95% confidence interval (CI), 1.09-1.89). The addition of an SSRI to NSAID therapy did not significantly increase the risk of UGIB (OR, 1.20; 95% CI, 0.78-1.92) over use of an NSAID alone. PPI co-therapy significantly reduced the risk of SSRI-related UGIB (OR, 0.39; 95% CI, 0.16-0.94). CONCLUSIONS: SSRI use is associated with a modestly increased risk of UGIB, which may be significantly reduced with PPI co-therapy. SSRI use is not a major risk factor for NSAID-related UGIB.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".