P-208 - Suicide by overdose in a bipolar disorder cohort
Bibliographic record
Abstract
Suicide rates are elevated among people with Bipolar Disorder (BD), yet there is limited research on the nature of suicide in this population. Intentional overdose (OD) is a common method of suicide, and the objective of this study was to characterize the specifics of OD suicides in a BD cohort, and compare with non-BD suicides. Coroner records for all cases of OD suicide in Toronto, Canada over a 10-year period (1998-2007) were examined. Data collected included demographics, psychiatric diagnosis and all substances present at lethal levels determined by the coroner to have caused death. Data analysis focused on comparisons between the BD cohort and non-BD suicides. Suicide by overdose was recorded in 34 people with BD (61.8% female) and 343 people without BD (46.9% female). There were numerous differences between the BD and non-BD suicide cohorts. The BD suicide group was younger, more likely to have made a prior suicide attempt, less likely to have a comorbid medical condition, and more likely to overdose on mood stabilizers or antipsychotics. Carbamazepine was the most frequently identified lethal substance among BD suicides (20.6%), with next most common being diphenhydramine (14.7%) and codeine (14.7%). Lithium was found at lethal levels in only one BD suicide (2.9%) and 3 non-BD suicides (0.9%). Key differences exist between BD and non-BD groups who suicide by OD, including the types of ingested medications. Improving our understanding of suicide in people with BD will ultimately aid in development of effective, targeted prevention strategies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".