Suicide risk in bipolar patients: the role of co‐morbid substance use disorders
Bibliographic record
Abstract
OBJECTIVE: Bipolar disorder is associated with a high frequency of both completed suicides and suicide attempts. The primary aim of this study was to identify clinical predictors of suicide attempts in subjects with bipolar disorder. METHODS: We studied 336 subjects with a diagnosis of bipolar I, bipolar II, or schizoaffective disorder (bipolar type). The Structured Clinical Interview for DSM-IV (SCID-I) was administered and subsequently two expert psychiatrists established a diagnosis. Predictors of suicide attempts were examined in attempters and non-attempters. RESULTS: The lifetime rate of suicide attempts for the entire sample was 25.6%. A lifetime co-morbid substance use disorder was a significant predictor of suicide attempts: bipolar subjects with co-morbid substance use disorders (SUD) had a 39.5% lifetime rate of attempted suicide, while those without had a 23.8% rate (odds ratio = 2.09, 95% CI = 1.03-4.21, chi2 = 4.33, df = 1, p = 0.037). CONCLUSIONS: Lifetime co-morbid SUD were associated with a higher rate of suicide attempts in patients with bipolar disorder. This relationship may have a genetic origin and/or be explained by severity of illness and trait impulsivity.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".