S639 Selective Serotonin Reuptake Inhibitors Increase Risk of Upper Gastrointestinal Bleeding When Used with NSAIDs: A Systemic Review and Meta-Analysis
Bibliographic record
Abstract
Introduction: The use of selective serotonin reuptake inhibitors (SSRIs) can increase the risk of upper gastrointestinal bleeding (UGIB) but reported results are heterogenous. In this study we aimed evaluate the risk of UGIB with SSRIs use in patients on NSAIDs. Methods: A comprehensive literature search was conducted using the SCOPUS and MEDLINE databases from inception through September 2020. Cohort and case-control studies that reported risk of UGIB in patient on NSAIDs with and without SSRIs were included. In phase I, title and abstracts were reviewed for study eligibility. In phase II, full manuscripts of potentially eligible studies were reviewed for eligibility. Newcastle-Ottawa checklist was used for study methodology quality assessment. Data extraction and quality assessment were performed in duplication, and any disagreements were resolved by consensus. The primary outcome was UGIB. Dichotomous data was pooled to calculate an odds ratio (OR) of the risk of UGIB in patients on NSAIDs with concomitant SSRI use. Results: Our search produced a total of 366 citations, and 21 were selected for full-text review. 1 cohort and 9 case-control studies were included in final analysis. On quality assessment scores are reported in Table 1. Use of SSRIs was associated with increased risk of UGIB in patients on NSAIDs with an OR 1.75, 95% CI=1.32-2.33. The number needed to harm for upper GI bleeding with SSRIs in patients on NSAIDs was 12. Conclusion: Moderate to good quality studies report significantly higher risk of UGIB with concomitant SSRIs use with NSAIDs. These observations have important clinical implications in choosing peptic ulcer prophylaxis.Table 1.: Study Methodology Quality Assessment on Newcastle-Ottawa Scale.Figure 1.: Risk of UGIB with and without SSRI Use Footnote: Forest Plot depicting OR of having UGIB with and without SSRI use in patients on NSAIDs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.013 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".