Prevention of suicidal behavior in bipolar disorder
Bibliographic record
Abstract
BACKGROUND: Excess mortality is a critical hallmark of bipolar disorder (BD) due to co-occurring general medical disorders and especially from suicide. It is timely to review of the status of suicide in BD and to consider the possibility of limiting suicidal risk. METHODS: We carried out a semi-systematic review of recent research reports pertaining to suicide in BD. FINDINGS: Suicide risk in BD is greater than with most other psychiatric disorders. Suicide rates (per 100,000/year) are approximately 11 and 4 in the adult and juvenile general populations, but over 200 in adults, and 100 among juveniles diagnosed with BD. Suicide attempt rates with BD are at least 20 times higher than in the adult general population, and over 50 times higher among juveniles. Notable suicidal risk factors in BD include: previous suicidal acts, depression, mixed-agitated-dysphoric moods, rapid mood-shifts, impulsivity, and co-occurring substance abuse. Suicide-preventing therapeutics for BD remain severely underdeveloped. Evidence favoring lithium treatment is stronger than for other measures, although encouraging findings are emerging for other treatments. CONCLUSIONS: Suicide is a leading clinical challenge for those caring for BD patients. Improved understanding of risk and protective factors combined with knowledge and close follow-up of BD patients should limit suicidal risk. Ethically appropriate and scientifically sound studies of plausible medicinal, physical, and psychosocial treatments aimed at suicide prevention specifically for BD patients are urgently needed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".