Ketamine for bipolar depression: an updated systematic review
Bibliographic record
Abstract
Background: The therapeutic potential of subanesthetic doses of ketamine appears promising in unipolar depression; however, its effectiveness in treating bipolar depression (BD) remains uncertain. Objective: This systematic review aimed to summarize findings on the use of ketamine for the treatment of BD by assessing its efficacy, safety, and tolerability. Design: Systematic review. Methods: We conducted a systematic review of studies that investigated the use of ketamine for adults with BD. We searched PubMed and Embase for relevant randomized-controlled trials, open-label trials, and retrospective chart analyses published from inception to 13 March 2023. Results: = 235; mean (SD) age: 45.55 (5.54)]. All participants who received intravenous (IV) ketamine were administered a dose of 0.5-0.75 mg/kg as an adjunctive treatment to a mood-stabilizing agent, whereas participants who received esketamine were administered a dosage ranging from 28 to 84 mg. Flexible dosing was used in real-world analyses. A total of 48% of participants receiving ketamine achieved a response (defined as ⩾50% reduction in baseline depression severity), whereas only 5% achieved a response with a placebo. Real-world studies demonstrated lower rates of response (30%) compared to the average across clinical trials (63%). Reductions in suicidal ideation were noted in some studies, although not all findings were statistically significant. Ketamine and esketamine were well tolerated in most participants; however, six participants (2% of the overall sample pool, 5 receiving ketamine) developed hypomanic/manic symptoms after infusions. Significant dissociative symptoms were observed at the 40-min mark in some trials. Conclusion: Preliminary evidence suggests IV ketamine as being safe and effective for the treatment of BD. Future studies should focus on investigating the effects of repeated acute and maintenance infusions using a randomized study design.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".