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Record W4410030943 · doi:10.1016/j.pnpbp.2025.111392

Longitudinal clinical outcomes based on cognitive and hippocampal clusters of first episode psychosis

2025· article· en· W4410030943 on OpenAlexafffund
Lucas Ronat, Delphine Raucher‐Chéné, Katie M. Lavigne, M. Mallar Chakravarty, Ridha Joober, Ashok Malla, Jai Shah, Martín Lepage

Bibliographic record

VenueProgress in Neuro-Psychopharmacology and Biological Psychiatry · 2025
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsMcGill University Health CentreMcGill UniversityDouglas Mental Health University Institute
FundersCanadian Institutes of Health Research
KeywordsPsychosisPsychologyCognitionPsychiatryHippocampal formationClinical psychologyNeuroscience

Abstract

fetched live from OpenAlex

In first episode psychosis (FEP), cognitive impairments are core features contributing to clinical and functional heterogeneity. Significant impairment indicates greater clinical severity throughout the course of the illness, particularly for negative symptoms. Hippocampal volume is smaller in FEP than in healthy controls (notably subfields like Cornu Ammonis 1–3 and subiculum), and is related to cognitive impairments and negative symptoms. The aim of this study was to compare the clinical and functional trajectories of FEP subgroups as a function of cognitive performance and hippocampal volumes. One hundred FEP patients and sixty healthy controls initially assessed using the CogState research battery, underwent 3 T MRI to extract hippocampal subfields and adjacent structures using the MAGeT brain algorithm. Clinical assessments were carried out for negative (Motivational and Pleasure – MAP, and diminished expression – EXP) and depressive symptoms, and global functioning. Measurements were taken at 4 time points (3, 9, 15, 21 months following program entry). Based on available first timepoint standardized cognitive and hippocampal features, using healthy controls as reference, clusters were determined by a hierarchical ascending classification. Their clinical and functional longitudinal trajectories were analyzed using linear mixed-effects models. Three baseline clusters were revealed: normal-range hippocampal volume with low attention, working and verbal memory (FEP 0), small hippocampus with low verbal memory and social cognition (FEP 1), and large hippocampus with low verbal memory (FEP 2). At baseline, the clusters did not differ on symptoms severity and global functioning. Longitudinally, MAP, EXP and depressive symptoms decreased over time in FEP 0. Global functioning improved in FEP 0 and FEP 1, while FEP 2 was clinically and functionally stable over time. Longitudinal inter-group comparisons did not yield any significant differences. The clusters were dissociated between hippocampus and cognition, but their trajectories suggest the importance of hippocampal integrity in the clinical and/or functional outcome. Future studies are needed to understand intervention efficiency depending on hippocampal integrity. • Different cognitive clusters were described in the first psychotic episode. Groups with more severe disorders had worse clinical outcomes. • Clinical outcome was also positively associated with hippocampal volumes. • The combined use of cognitive performance and hippocampal volume has enabled new clusters to be established. • The cluster with normal range hippocampus subfields and low cognition improved over time. • This suggests that preserved hippocampus might lead to a better recovery from symptoms and global functioning despite poor cognitive performance.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.046
GPT teacher head0.413
Teacher spread0.367 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations0
Published2025
Admission routes2
Has abstractyes

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