A magnetic resonance imaging study of mood stabilizer‐ and neuroleptic‐naïve first‐episode mania
Bibliographic record
Abstract
Objectives: Patients with bipolar disorder have changes in brain structures but it is unclear if these are present at disease onset and thus predispose subjects to develop the disorder, or whether they develop during the course of the disorder, either due to the effects of multiple episodes or as a consequence of treatment with psychotropic agents. Studies in first‐episode (FE) manic patients have the potential to provide answers to these questions. Methods: Voxel‐based morphometry (VBM) was used to assess magnetic resonance imaging scans of 15 FE manic patients and 15 matched healthy controls. Results: Using a priori defined statistical criteria, no significant differences in brain structures were noted between the two groups. However, there was approximately a 6% reduction in left anterior cingulate, left precuneus and right posterior cingulate volume in FE patients and these reductions were significant (p ≤ 0.002) at uncorrected levels. Conclusions: First‐episode manic patients have reductions in left anterior, right posterior cingulate as well as left precuneus volumes, but these reductions are smaller and likely worsen with further mood episodes in bipolar patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".