Pharmacotherapy of high-risk population for developing psychosis
Bibliographic record
Abstract
ABSTRACT: Early interventions in high-risk population for psychotic disorder target both conversion rates and functional impairments. Existing guidelines (European Psychiatric Association, NICE, Canadian) do not consider drug treatment as the first-line choice, pharmaceuticals mostly complement least restrictive, non-pharmacological approaches (e.g., CBT). Pharmacotherapy can address existing specific symptoms (mood fluctuations, anxiety, subclinical brief or attenuated psychotic symptoms); it is reserved mainly for individuals with more severe symptoms, those that do not respond to psychological treatments or are escalating. There are only a few randomized controlled trials with antipsychotics (olanzapine, risperidone, aripiprazole, ziprasidone, amisulpride), either as a monotherapy or in combination with other interventions. The results did not show a superiority of drug therapy in prevention of transition to psychosis over alternative strategies; long-term antipsychotic treatment with a primarily preventive aim is not generally recommended. Other pharmacological interventions also include experimental drugs or food supplements (omega-3 polyunsaturated fatty acids, cannabidiol, D-serine). DISCLOSURE OF INTEREST: None Declared
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".