Suicidal Ideation and Suicide Completion in Benzodiazepine Users: A Systematic Review of Current Evidence
Bibliographic record
Abstract
Benzodiazepines (BZDs) are widely used anxiolytics for treating various psychiatric conditions and for procedures requiring conscious sedation. Despite their therapeutic benefits, there is concern about their paradoxical effects, particularly the potential increase in suicidal ideation and suicide completion. This systematic review examines the extent to which benzodiazepines contribute to, cause, or exacerbate suicidal ideation and suicide completion. Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, we conducted a systematic review of literature from databases including PubMed, PubMed Central (PMC), and PubPsych. Search terms related to benzodiazepines and suicide were used, yielding 7,961 articles. After removing duplicates and applying inclusion and exclusion criteria, 587 articles were screened, leading to a final selection of six articles. These studies underwent rigorous quality assessment using various tools. The review highlighted several key findings. Moderate benzodiazepine use with concomitant psychotherapy or antidepressants was associated with reduced suicide risk. Concurrent use of opioids and benzodiazepines significantly elevated the risk of suicide attempts and intentional self-harm. Benzodiazepine use was linked to increased suicide risk in vulnerable groups, including those with pre-existing mental health conditions. Benzodiazepines should be prescribed with caution, ideally for short-term use until antidepressant effects manifest. Close monitoring for addiction, withdrawal, and suicidal ideation is essential. Prescribers must be aware of the increased risks when benzodiazepines are used in conjunction with opioids or in patients with heightened vulnerability to suicide. Effective weaning programs and risk assessment tools are crucial to mitigate these risks and ensure patient safety.
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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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.010 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".