The efficacy and safety of adjunctive intranasal esketamine treatment in major depressive disorder: a systematic review and meta-analysis
Bibliographic record
Abstract
Intranasal (IN) esketamine represents an innovative treatment for individuals with treatment resistant depression and depression with suicidal ideation and behavior. Herein, we synthesize extant long-term studies (≥ 4 weeks) regarding this treatment. The interventional studies of IN esketamine in patients with depression having a study period of at least four weeks were included for our synthesis. A meta-analysis was undertaken for the efficacy and safety parameters of adjunctive IN esketamine vs IN placebo with an oral antidepressant. The data excluded from meta-analysis were synthesized narratively. After pooling data from seven randomized controlled trials, treatment with adjunctive IN esketamine vs IN placebo was safe overall, and more effective at decreasing depressive symptoms (d = −0.239; 95%CI = −0.335,-0.142;p < 0.0001), with higher response (RR = 1.221; 95% CI = 1.055,1.428; p = 0.017) and remission (RR = 1.366; 95% CI = 1.182,1.578; p < 0.0001) rates. The year-long trials showed that treatment with adjunctive IN esketamine led to lower relapse rates with no considerable long-term side effects. Intranasal esketamine was demonstrated to be safe, well tolerated, and rapidly effective in individuals with treatment resistant depression, suicidal ideation, and suicidal behavior.
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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) | 0.018 | 0.030 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".