The effect of second-generation antipsychotics on hippocampal volume in first episode of psychosis: longitudinal study
Bibliographic record
Abstract
BACKGROUND: Current neuroscience literature has related treatment with aripiprazole to improved memory performance and subcellular changes in the hippocampus. AIMS: To explore the volumetric changes in hippocampal grey matter in people with a first episode of psychosis (FEP) treated with second-generation antipsychotics. METHOD: =44). RESULTS: 's<0.040). CONCLUSIONS: Aripiprazole is a first-line, second-generation treatment option that may provide an added benefit of pro-hippocampal growth. The biological underpinnings of these changes should be the focus of future investigations and may be key towards achieving a better clinical outcome for more individuals. DECLARATION OF INTEREST: M.L. received financial assistance/compensation for research and educational events from Janssen-Ortho, Eli Lilly, Roche and Otsuka/Lundbeck Alliance. A.K.M. received financial assistance/compensation for research and educational activities from Pfizer, Janssen-Ortho, AstraZeneca and Bristol-Myers Squibb. R.J. received consultancy honorariums from Pfizer and Janssen-Ortho. COPYRIGHT AND USAGE: © The Royal College of Psychiatrists 2016. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) licence.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".