Ketamine in the Treatment of Obsessive-Compulsive Disorder: A Systematic Review
Bibliographic record
Abstract
INTRODUCTION: First-line treatment for obsessive-compulsive disorder (OCD) includes exposure and response prevention behavioral therapy and serotonin reuptake inhibitors, particularly in combination. New and more effective treatments are needed, give that recent studies suggest that glutamatergic neurotransmission contributes to the pathophysiology of the disorder. In these circumstances, ketamine, as a potent N-methyl-D-aspartate receptor antagonist and glutamate modulator, offers alternative possibilities for OCD treatment. METHODS: This systematic review aims to investigate the effects of ketamine in OCD, following the Preferred Reporting Items for Systematic Review and Meta-analyses Protocols (PRISMA-P). Searches were carried out using the PubMed/MEDLINE, Embase, and PsycINFO databases. RESULTS: Nine articles were included, of which three were randomized controlled trials, three case reports, two open-label trials, and one a retrospective chart review. Reported data have shown a potential for fast onset of action and good tolerability of ketamine for OCD, even though the principal studies used only single-session racemic ketamine treatments, administered intravenously, and the results have been erratic. In addition, none of the available evidence demonstrates whether racemic ketamine, S-ketamine, or R-ketamine has the best efficacy in controlling OCD symptoms, and only sparse evidence suggests that a combination of ketamine and psychotherapy could benefit patients with OCD. CONCLUSION: In order to advance clinical practice regarding the use of ketamine in treating OCD, future randomized, double-blind, placebo-controlled trials are required. These trials need to use larger samples to explore ketamine and its enantiomers, with different methods of administration, multiple sessions, and appropriate washout periods.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".