Olanzapine in the treatment of schizophrenia in adolescents – mechanisms of action and therapeutic efficacy.
Bibliographic record
Abstract
BACKGROUND: Olanzapine is widely used for schizophrenia and bipolar I disorder, yet its role in adolescents remains debated due to metabolic risks. OBJECTIVE: To review mechanisms, efficacy, safety, pharmacokinetics, and guideline positions of olanzapine in youth, with comparison to adults. METHODS: Narrative synthesis of randomized trials, open-label studies, meta-analyses, and major guidelines (APA, NICE, Canadian), with focused appraisal of pediatric data. RESULTS: Olanzapine's multi-receptor antagonism (D₂, 5-HT₂A/2C, H₁, muscarinic, α₁) underpins robust antipsychotic effects. In adolescents, short-term RCTs show significant improvement in PANSS/BPRS-C and YMRS versus placebo; efficacy is broadly comparable to risperidone and aripiprazole. Pharmacokinetics are similar to adults, though exposure is ~27-34% higher in youth. Adverse effects-especially weight gain, dyslipidemia, hyperprolactinemia, and glycemic abnormalities-are more pronounced in adolescents. Guidelines endorse olanzapine as an option for schizophrenia and as first-line for acute mania; OFC is recommended for bipolar depression by most but not NICE. LAI olanzapine is not approved <18 years. CONCLUSIONS: Olanzapine is effective in adolescent psychosis and mania but carries substantial metabolic liability. Given no clear efficacy advantage over other SGAs, it is best positioned as a second-line agent in youth, with preference for monotherapy, cautious dosing, and stringent metabolic monitoring. Evidence for benefits on negative and cognitive symptoms in adolescents remains limited.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".