Predictors of Future Suicide Attempts Among Individuals Referred to Psychiatric Services in the Emergency Department
Bibliographic record
Abstract
This study examined which factors predict future suicide attempts (SAs) among people referred to psychiatric services in the emergency department (ED). It included consecutive adult (age >18 years) presentations (N = 6919) over a 3-year period to the two tertiary care hospitals in Manitoba, Canada. Medical professionals assessed each individual on 19 candidate risk factors. Stepwise logistic regression and receiver operating characteristic curves examined the association between the baseline variables and future SAs within the next 6 months. A total of 104 individuals re-presented to the ED with future SAs. Of the 19 baseline variables, only two independently accounted for the variance in future attempts. High-risk scores using this two-item model were associated with elevated odds of future SA (odds ratio, 3.22; 95% confidence interval, 1.62-6.42; p < 0.01), but this was tempered by a low positive predictive value. Further evaluation is required to determine if this two-item tool could help identify people requiring more comprehensive risk assessment referred to psychiatry in the ED.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".