Use of benzodiazepines in obsessive–compulsive disorder
Bibliographic record
Abstract
This study aimed to determine the frequency of benzodiazepine (BDZ) use in a large sample of patients with obsessive-compulsive disorder (OCD) and ascertain the type of BDZ used and the correlates and predictors of BDZ use in OCD. The sample consisted of 955 patients with OCD from a comprehensive, cross-sectional, multicentre study conducted by the Brazilian Research Consortium on Obsessive-Compulsive Spectrum Disorders between 2003 and 2009. The rate of BDZ use over time in this OCD sample was 38.4%. Of individuals taking BDZs, 96.7% used them in combination with other medications, usually serotonin reuptake inhibitors. The most commonly used BDZ was clonazepam. Current age, current level of anxiety and number of additional medications for OCD taken over time significantly predicted BDZ use. This is the first study to comprehensively examine BDZ use in OCD patients, demonstrating that it is relatively common, despite recommendations from treatment guidelines. Use of BDZs in combination with several other medications over time and in patients with marked anxiety suggests that OCD patients taking BDZs may be more complex and more difficult to manage. This calls for further research and clarification of the role of BDZs in the treatment of OCD.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".