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A magnetic resonance imaging study of mood stabilizer‐ and neuroleptic‐naïve first‐episode mania

2007· article· en· W2082910689 on OpenAlexaff
Lakshmi N. Yatham, In Kyoon Lyoo, Peter F. Liddle, Perry F. Renshaw, Dante D. C. Wan, Raymond W. Lam, Jaeuk Hwang

Bibliographic record

VenueBipolar Disorders · 2007
Typearticle
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsManiaPrecuneusBipolar disorderMagnetic resonance imagingPsychologyMoodPosterior cingulateNeuroimagingCardiologyInternal medicinePsychiatryMedicineNeuroscienceFunctional magnetic resonance imagingRadiology

Abstract

fetched live from OpenAlex

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<or=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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.182
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.239
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations58
Published2007
Admission routes1
Has abstractyes

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