Antipsychotic Exposure in Clinical High Risk of Psychosis
Bibliographic record
Abstract
Objective: Current treatment guidelines for individuals at clinical high risk (CHR) for psychosis do not recommend the prescription of antipsychotics (not even second-generation ones) as the first treatment option for preventing psychosis. Yet, recent meta-analytic evidence indicates that antipsychotic exposure in CHR is relatively widespread and associated with a higher imminent risk of transition to psychosis. Therefore, we undertook this study to better delineate which clinical characteristics of CHR individuals may lead to the choice of antipsychotic prescription and whether it identifies a subgroup at higher risk for conversion to psychosis. Methods: Consecutively referred CHR individuals (N = 717) were assessed for demographic and clinical characteristics and followed up for 3 years (200 did not reach the end of the follow-up time) from 2016 to 2021. The sample was then dichotomized, on the basis of antipsychotic prescription, to prescribed (CHRAP+, n = 492) or not-prescribed (CHRAP–, n = 225) groups, which were subsequently compared for sociodemographic and clinical characteristics. The risks of conversion to psychosis in CHRAP+ versus CHRAP– groups were tested via survival analysis. Results: Of the 717 CHR individuals, 492 (68.62%) were prescribed antipsychotics; among these antipsychotics, the highest proportion used was for aripiprazole (n = 152), followed by olanzapine (n = 106), amisulpride (n = 76), and risperidone (n = 64). The CHRAP+ group had younger age (t = 2.138, P = .033), higher proportion of female individuals (χ2 = 5.084, P = .024), psychotic symptoms of greater severity (t = 7.910, P < .001), and more impaired general function (t = 5.846, P < .001) than the CHRAP– group. The CHRAP+ group had greater risk for conversion to psychosis (27.0% in the CHRAP+ group vs 10.9% in the CHRAP– group, P < .001). Factors related to positive symptoms were the most likely to influence doctors’ decision-making regarding prescripton of antipsychotics, without influence of age, sex, and education levels. Conclusions: Clinicians may prescribe antipsychotics mainly based on the severity of positive and disorganization symptoms of CHR individuals. The CHRAP+ group was associated with a higher risk of conversion to psychosis. In pragmatic terms, this finding indicates that baseline antipsychotic prescription in CHR cohorts is a warning flag for higher incipient risk of psychosis and designates as hyper-CHR subgroup as compared to antipsychotic-naive CHR. Trial Registration: ClinicalTrials.gov identifier: NCT04010864
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".