Ketamine Treatment in Depression: A Systematic Review of Clinical Characteristics Predicting Symptom Improvement
Bibliographic record
Abstract
Ketamine has been shown to be efficacious for the treatment of depression, specifically among individuals who do not respond to first-line treatments. There is still, however, a lack of clarity surrounding the clinical features and response periods across samples that respond to ketamine. This paper systematically reviews published randomized controlled trials that investigate ketamine as an antidepressant intervention in both unipolar and bipolar depression to determine the specific clinical features of the samples across different efficacy periods. Moreover, similarities and differences in clinical characteristics associated with acute versus longer-term drug response are discussed. Similarities across all samples suggest that the population that responds to ketamine's antidepressant effect has experienced chronic, long-term depression, approaching ketamine treatment as a "last resort". Moreover, differences between these groups suggest future research to investigate the potential of stronger efficacy towards depression in the context of bipolar disorder compared to major depression, and in participants who undergo antidepressant washout before ketamine administration. From these findings, suggestions for the future direction of ketamine research for depression are formed.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".