Efficacy of orexin antagonists for the management of major depressive disorder: A systematic review of randomized clinical trials
Bibliographic record
Abstract
Orexin receptor antagonists are a group of medications primarily developed to treat insomnia. Preliminary studies support their efficacy in the treatment of depression. In this systematic review, we aim to evaluate the efficacy of orexin receptor antagonists for the treatment of major depressive disorder (MDD). Electronic databases were searched from inception to February 2024 to find relevant studies. Original studies in English that evaluated efficacy of orexin receptor antagonists were included. A total of five randomized clinical trials involving 498 participants were included. Seltorexant (20 mg) significantly decreased depression scores when compared to placebo, as measured by the Hamilton Depression Rating Scale (HDRS). In patients with inadequate responses to antidepressants, seltorexant (20 mg) also showed improvement in Montgomery-Ǻsberg Depression Rating Scale (MADRS) total scores compared to placebo. However, filorexant did not exhibit a significant difference in MADRS total scores compared to placebo. A separate study on seltorexant (40 mg) for MDD patients resulted in a non-significant decrease in depressive symptoms compared to placebo, as measured by the Quick Inventory of Depressive Symptomatology - Self-Report (QIDS-SR). Taken together, these findings highlight the potential of orexin receptor antagonists, particularly seltorexant, as a novel avenue for managing depressive symptoms in MDD. Further research is warranted to better understand their role in depression treatment and their safety profile.
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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 | 0.007 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".