Efficacy and Tolerability of Combination Treatments for Major Depression: Antidepressants plus Second-Generation Antipsychotics vs. Esketamine vs. Lithium
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: efficacy and tolerability remain inadequately tested. In particular, the value and safety of increasingly employed second-generation antipsychotics (SGAs) and new esketamine, compared to lithium as antidepressant adjuncts remain unclear. METHODS: We reviewed randomized, placebo-controlled trials and used random-effects meta-analysis to compare odds ratio (OR) versus placebo, as well as numbers-needed-to-treat (NNT) and to-harm (NNH), for adding SGAs, esketamine, or lithium to antidepressants for major depressive episodes. RESULTS: Analyses involved 49 drug-placebo pairs. By NNT, SGAs were more effective than placebo (NNT = 11 [CI: 9-15]); esketamine (7 [5-10]) and lithium (5 [4-10]) were even more effective. Individually, aripiprazole, olanzapine+fluoxetine, risperidone, and ziprasidone all were more effective (all NNT < 10) than quetiapine (NNT = 13), brexpiprazole (16), or cariprazine (16), with overlapping NNT CIs. Risk of adverse effects, as NNH for most-frequently reported effects, among SGAs versus placebo was 5 [4-6] overall, and highest with quetiapine (NNH = 3), lowest with brexpiprazole (19), 5 (4-6) for esketamine, and 9 (5-106) with lithium. The risk/benefit ratio (NNH/NNT) was 1.80 (1.25-10.60) for lithium and much less favorable for esketamine (0.71 [0.60-0.80]) or SGAs (0.45 [0.17-0.77]). CONCLUSIONS: Several modern antipsychotics and esketamine appeared to be useful adjuncts to antidepressants for acute major depressive episodes, but lithium was somewhat more effective and better tolerated. LIMITATIONS: Most trials of adding lithium involved older, mainly tricyclic, antidepressants, and the dosing of adjunctive treatments were not optimized.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it