Strategies to mitigate dissociative and psychotomimetic effects of ketamine in the treatment of major depressive episodes: a narrative review
Bibliographic record
Abstract
Objectives Replicated evidence has demonstrated that ketamine exerts rapid-acting and potent antidepressant effects. Notwithstanding, its promise to mitigate depressive symptoms and suicidality in antidepressant-resistant populations, several limitations and safety concerns accompany ketamine including, but not limited to, the potential for abuse and psychotomimetic/dissociative experiences. The focus of the current narrative review is to synthesise available evidence of strategies that may mitigate and fully prevent treatment-emergent psychotomimetic and dissociative effects associated with ketamine administration. Methods PubMed, Google Scholar and ClinicalTrials.gov were searched for relevant articles. Results Potential avenues investigated to minimise psychotomimetic effects associated with ketamine administration include the following: (1) altering dosing and infusion rates; (2) route of administration; (3) enantiomer choice; (4) co-administration with mood stabilisers of antipsychotics; and (5) use of alternative N-methyl-d-aspartate (NMDA)-modulating agents. Emerging evidence indicates that dissociative experiences can be significantly mitigated by using an intranasal route of administration, lower dosages, or use of alternative NMDA-modulating agents, namely lanicemine (AZD6765) and GLYX-13. Conclusions Currently, intranasal administration presents as the most promising strategy to mitigate dissociative and psychotomimetic effects; however, studies of strategies to mitigate the adverse events of ketamine are limited in number and quality and thus further investigation is still needed.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".