Esketamine for treatment resistant depression
Bibliographic record
Abstract
Introduction: Treatment Resistant Depression (TRD) is a common and burdensome condition with poor outcomes and few treatment options. Esketamine is the S-enantiomer of ketamine and has recently been FDA approved in the United States for treating depression that has failed to respond to trials of two or more antidepressants.Areas covered: This review will briefly discuss current treatment options for TRD, then review esketamine. Relevant literature was identified through online database searches, and clinical trial data were provided by Janssen Pharmaceuticals. Pharmacology, including kinetics and dynamics, is discussed, then clinical data regarding efficacy and safety for esketamine from Phase 2–3 trials are reviewed.Expert opinion: In the expert opinion, the authors discuss multiple factors including patient, physician, and social factors that will influence the use of esketamine. While the efficacy of esketamine compared to off-label use of racemic ketamine remains unclear, both esketamine’s approval for use in TRD and longer-term safety data may position it preferentially above racemic ketamine, although factors such as cost and monitoring requirements may limit its use. While questions remain regarding duration and frequency of treatment, as well as addictive potential, esketamine is a novel treatment option offering new hope for TRD.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".