Sex differences in the clinical characteristics of suicide among individuals with bipolar disorder: An observational study of coroner data in Toronto
Bibliographic record
Abstract
INTRODUCTION: The risk of suicide in bipolar disorder (BD) is 10-30× higher and the male-to-female ratio of suicide is narrower than that of the general population. This study examined sex differences in the correlates of suicide deaths among individuals with BD. METHODS: All cases of suicide deaths identified by the Office of the Chief Coroner (OCC) occurring in the City of Toronto between 1998 and 2020 were included and stratified by presence of a BD diagnosis. Sex differences in demographic, clinical, and suicide-related variables were examined between (i.e. BD vs. non-BD) and within (i.e. sex differences in BD) diagnostic categories. Variables significant in univariate analysis were analyzed for sex-by-diagnosis interaction effects using binary logistic regression. RESULTS: Among the 5285 suicide deaths, the male-to-female ratio of suicide decedents was narrower among the BD (1.4:1), compared to the non-BD group (2.5:1). Sex differences were largely similar between BD and non-BD groups. Females with BD less frequently experienced a bereavement stressor (OR = 0.33, 95 % CI [0.11, 0.97]) and more frequently left a suicide note (OR = 2.16, 95 % CI [1.16, 4.04]) than any other group. CONCLUSION: The male-to-female ratio was narrower among BD suicide decedents, replicating previous findings. Females with BD were more likely than any other group to leave a suicide note, whereas females without BD were more likely than any other group to experience bereavement stress. Future research should explore sex differences in other factors that may contribute to increased suicide risk among females with BD.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".