Oral ketamine for depression: An updated systematic review
Bibliographic record
Abstract
Objectives: Ketamine is a glutamate N-methyl-D-aspartate receptor antagonist that can be used to treat major depressive disorder by single or repeated infusions. However, the accessibility and scalability of oral ketamine make it preferred over intravenous ketamine. In this systematic review, we aim to evaluate the efficacy, tolerability, and safety of oral ketamine, esketamine and r-ketamine for unipolar and bipolar depression. Materials and methods: Electronic databases were searched from inception to September 2022 to identify relevant articles. Results: Twenty-two studies, including four randomized clinical trials (RCTs), one case series, six case reports, five open-label trials and six retrospective chart review studies involving 2336 patients with depression were included. All included studies reported significant improvement following ketamine administration. Ketamine was well tolerated without serious adverse events. However, RCTs had a high risk of bias due to analysis methods and adverse events monitoring. Ketamine dosage varied from 0.5 to 1.25 mg/kg. The frequency of administration was daily to monthly. Several important limitations were identified, most notably the small number of RCTs. Conclusions: Taken together, preliminary evidence suggests the potential for antidepressant effect of oral ketamine. However, further research with large sample size and long follow-up period is needed to better determine the antisuicidal effect and efficacy in treatment-resistant depression.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.006 | 0.007 |
| 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) | 0.007 | 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".