Understanding the effects of chronic benzodiazepine use in depression: a focus on neuropharmacology
Bibliographic record
Abstract
Benzodiazepines are frequently prescribed on an ongoing basis to individuals with depression, mainly to alleviate anxiety or insomnia, despite current guideline recommendations that continuous use should not exceed 4 weeks. Currently, there are no efficacy trials published beyond 8 weeks. Several antidepressant trials demonstrate that the concomitant use of a benzodiazepine is associated with poorer depressive outcomes and functional status; however, it is unclear why this is the case. Patients with depression receiving a benzodiazepine may reflect a more ill or high anxiety group, although even within anxiety disorders, the use of a benzodiazepine is associated with poorer outcomes. The neuroadaptive consequences of long-term benzodiazepine use may be a factor underlying these findings. Chronic benzodiazepine use results in decreased gamma-aminobutyric acid and monoaminergic function, as well as interference with neurogenesis, which are all purported to play a role in antidepressant efficacy. This review will discuss the oppositional neuropharmacological interactions between chronic benzodiazepine use and antidepressant mechanism of action, which could result in reduced antidepressant efficacy and function in depression.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".