SSRIs associated with increased risk of brain haemorrhage, but absolute risks low
Bibliographic record
Abstract
Question: Is there an association between selective serotonin reuptake inhibitors (SSRIs) and the incidence of brain haemorrhage? Outcomes: Incidence of intracerebral haemorrhage, intracranial haemorrhage, subarachnoid haemorrhage or haemorrhagic stroke (subarachnoid haemorrhage plus intracerebral haemorrhage). Design: Systematic review with meta-analysis. Data sources: MEDLINE, EMBASE, Web of Science Conference Proceedings, SCOPUS, ProQuest and dissertations were searched for controlled observational studies (search dates not stated). Reference lists of identified studies were hand searched. Study selection and analysis: Studies were included if they had a control group not taking SSRIs and were a prospective or retrospective cohort study, case–crossover or case–control study reporting risks of brain haemorrhage associated with SSRIs. Study results were pooled using DerSimonian and Laird fixed effect rate ratios. Results from adjusted and unadjusted analyses were pooled separately. Random effects models were used for sensitivity analysis. Heterogeneity was assessed using the I2 statistic. Duval-and-Tweedie trim-and-fill analyses were used to assess the possibility of publication bias. Risks of haemorrhage with exposure … Correspondence to Mathison Centre for Mental Health Research and Education, Rm # 4D64, TRW Building, 3280 Hospital drive NW, Calgary, Alberta, Canada T2N4Z6; rramasub{at}ucalgary.ca
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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 | 0.014 | 0.093 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.008 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".