Efficacy and Safety of Antipsychotics for the Treatment of Major Depressive Disorder in Adolescents and Adults: Current Issues and Clinical Perspective
Bibliographic record
Abstract
Objectives: Atypical antipsychotics are increasingly being prescribed for the treatment of mood disorders, often off-label. This review describes existing published literature on the efficacy and safety of antipsychotics for the treatment of major depressive disorder (MDD) in adults and adolescents. We discuss current clinical considerations: role as monotherapy, adjunctive, or augmentation therapy, side effect profiles, and optimal dose and duration of therapy. Potential areas for future research and methodological considerations are also highlighted. Method: We conducted a literature search of MEDLINE, EMBASE, PsycINFO, and Cochrane databases. Relevant articles and references were identified. MDD practice guidelines for adolescents and adults were reviewed. Results: Evidence for using atypical antipsychotics to treat MDD is heterogeneous. It is thus difficult to draw firm conclusions regarding their role in therapy. Most current guidelines do not include recommendations for atypical antipsychotics, but off-label use is common in clinical practice. Primary use is adjunct or augmentation therapy for treatment resistant depression. Potential benefits versus side effects must be cautiously considered, especially for children and adolescents. Clinicians must rely on their clinical experience and professional judgment to determine an optimal dose and duration of therapy. Conclusions: There is progressive research to support the use of atypical antipsychotics to treat MDD in adults. However, additional research and well-designed studies are needed to determine the appropriate and safe use of atypical antipsychotics for treating child and adolescent depression. Other subpopulations that may benefit from combination therapy, such as individuals with dual diagnoses, may be identified through future research.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".