Risks of Suicide and Poisoning Among Elderly Patients Prescribed Selective Serotonin Reuptake Inhibitors
Bibliographic record
Abstract
BACKGROUND: Treatment with selective serotonin reuptake inhibitors (SSRIs) has been associated with increased suicide risk. Risks of suicide death and of poisoning were compared during periods of SSRI treatment versus periods without any antidepressant treatment among elderly patients. METHOD: In this retrospective cohort study, records from the Quebec Health Care Fund and Vital Statistics databases were obtained for patients 65 years and older who had filled a prescription for an SSRI between January 1998 and December 2004. Patients were followed from the filling date of the first SSRI prescription during the study period until death, the end of the first period extending for at least 365 days with no antidepressant supply, or December 31, 2004, whichever occurred first. RESULTS: The cohort included 128,229 patients (mean age = 75.4 years), 70% of whom were women. Numbers of suicide deaths (crude rate/100,000 patient-years) were 37 (23) during SSRI use, 16 (51) during other antidepressant use, 5 (54) during use of both an SSRI and another anti-depressant, and 29 (29) during no antidepressant use. The adjusted risk of suicide death (Cox regression model with time-dependent exposure) was not higher during SSRI use versus nonuse (hazard ratio [95% CI]): any SSRI = 0.64 (0.38 to 1.07), paroxetine = 0.71 (0.37 to 1.35), citalopram = 1.16 (0.59 to 2.25), and sertraline = 0.38 (0.16 to 0.93). The adjusted hazard ratio (95% CI) of poisoning was higher during SSRI use versus nonuse (1.16 [1.07 to 1.25]) and varied between SSRI agents from 0.93 (0.74 to 1.16) for fluoxetine to 1.45 (1.23 to 1.71) for fluvoxamine. CONCLUSION: Among elderly patients dispensed SSRIs, the risk of suicide death was not higher during periods of SSRI use compared to when antidepressants were not being used.
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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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".