Effectiveness of Antipsychotics in Reducing Suicidal Ideation: Possible Physiologic Mechanisms
Bibliographic record
Abstract
Background: The aim of this study is to evaluate whether any specific antipsychotic regimen or dosage is effective in managing suicidal ideation in schizophrenia. Four comparisons were conducted between: (1) clozapine and other antipsychotics; (2) long-acting injectable and oral antipsychotics; (3) atypical and typical antipsychotics; (4) antipsychotics augmented with antidepressants and antipsychotic treatment without antidepressant augmentation. Methods: We recruited 103 participants diagnosed with schizophrenia spectrum disorders. Participants were followed for at least six months. The Beck Scale for Suicidal Ideation (BSS) was used to assess the severity of suicidal ideation at each visit. We performed a multiple linear regression model controlling for BSS score at study entry and other confounding variables to predict the change in the BSS scores between two visits. Results: Overall, there were 28 subjects treated with clozapine (27.2%), and 21 subjects with depot antipsychotics (20.4%). In our sample, 30 subjects experienced some suicidal ideation at study entry. When considering the entire sample, there was a statistically significant decrease in suicidal ideation severity in the follow-up visit compared to the study entry visit (p = 0.043). Conclusions: To conclude, our preliminary analysis implies that antipsychotics are effective in controlling suicidal ideation in schizophrenia patients, but no difference was found among alternative antipsychotics’ classes or dosages.
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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) | 0.000 | 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".