Nitrous oxide for the treatment of psychiatric disorders: A systematic review of the clinical trial landscape
Bibliographic record
Abstract
Abstract Objective To systematically review published research studies and ongoing clinical trials investigating nitrous oxide (N 2 O) in psychiatric disorders, providing an up‐to‐date snapshot of the clinical research landscape. Methods A comprehensive literature search was conducted for studies published until June 2021 using the OVID databases (MEDLINE, Embase, APA PsycInfo) and the clinical trial registries (ClinicalTrials.gov, ICTRP). Results In total, five relevant published articles were identified, among which four investigated N 2 O for depression. One single‐dose randomized controlled trial (RCT) for treatment‐resistant depression (TRD), one triple crossover RCT comparing 50% vs. 25% N 2 O for TRD, and one repeated‐dose RCT for major depressive disorder (MDD) suggest that N 2 O has preliminary feasibility with rapid‐acting effects on symptoms of depression. From the public registries, 10 relevant ongoing clinical trials were identified. They aim to explore the use of N 2 O for MDD, post‐traumatic stress disorder, bipolar disorder, obsessive‐compulsive disorder, and suicidal ideation. To date, the typical treatment protocol parameters were a single session of 50% N 2 O delivered for 60 min, although the concentration of 25% is also being explored. Projected enrolment numbers for ongoing trials ( M = 55.0) were much higher than sample sizes for published studies ( M = 13.0), suggesting that there potentially will be more large‐scale RCTs published in the next few years. Conclusion Preliminary studies support the feasibility of administering N 2 O for depression; however, appropriate blinding is a critical challenge. Larger‐scale RCTs with repeated doses of N 2 O and follow‐up times beyond 1 month are needed to confirm the feasibility, therapeutic efficacy, and sustainability of response.
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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 | 0.022 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.007 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".