Ketamine for the Treatment of Psychiatric Disorders: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Inadequate response to first- and second-line pharmacological treatments for psychiatric disorders is commonly observed. Ketamine has demonstrated efficacy in treating adults with treatment-resistant depression (TRD), with additional off-label benefits reported for various psychiatric disorders. Herein, we performed a systematic review and meta-analysis to examine the therapeutic applications of ketamine across multiple mental disorders, excluding mood disorders. METHODS: We conducted a multidatabase literature search of randomized controlled trials and open-label trials investigating the therapeutic use of ketamine in treating mental disorders. Studies utilizing the same psychological assessments for a given disorder were pooled using the generic inverse variance method to generate a pooled estimated mean difference. RESULTS: The search in OVID (MedLine, Embase, AMED, PsychINFO, JBI EBP Database), EBSCO CINAHL Plus, Scopus, and Web of Science yielded 44 studies. Ketamine had a statistically significant effect on PTSD Checklist for DSM-5 (PCL-5) scores (pooled estimate = ‒28.07, 95% CI = [‒40.05, ‒16.11], p < 0.001), Clinician-Administered PTSD Scale for DSM-5 (CAPS-5) scores (pooled estimate = ‒14.07, 95% CI = [‒26.24, ‒1.90], p = 0.023), and Yale-Brown Obsessive Compulsive Scale (Y-BOCS) scores (pooled estimate = ‒8.08, 95% CI = [‒13.64, ‒2.52], p = 0.004) in individuals with PTSD, treatment-resistant PTSD (TR-PTSD), and obsessive compulsive disorder (OCD), respectively. For alcohol use disorders and at-risk drinking, there was disproportionate reporting of decreased urge to drink, increased rate of abstinence, and longer time to relapse following ketamine treatment. CONCLUSIONS: Extant literature supports the potential use of ketamine for the treatment of PTSD, OCD, and alcohol use disorders with significant improvement of patient symptoms. However, the limited number of randomized controlled trials underscores the need to further investigate the short- and long-term benefits and risks of ketamine for the treatment of psychiatric disorders.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.026 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".