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Record W2602133448 · doi:10.1093/schbul/sbx022.085

M90. Associations of Cortical Thickness With Awareness of Illness in Enduring Schizophrenia

2017· article· en· W2602133448 on OpenAlexaff
Sophie Béland, Lisa Buchy, Ashok Malla, Ridha Joober, Norbert Schmitz, Martín Lepage

Bibliographic record

VenueSchizophrenia Bulletin · 2017
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsUniversity of CalgaryDouglas Mental Health University InstituteMcGill University
Fundersnot available
KeywordsSchizophrenia (object-oriented programming)PsychologyNeuropsychologyNeural correlates of consciousnessClinical psychologyCategorical variableNeuroimagingAssociation (psychology)Frontal cortexPsychiatryDevelopmental psychologyCognitionNeuroscience

Abstract

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Background: The relationship between poor insight and less favorable outcomes in schizophrenia has led to research efforts to understand its neurobiological basis. Thus far, research on the neural correlates of insight has been restricted by small sample sizes and a focus on regions of interest related to neuropsychological theories of insight. Moreover, few studies have assessed the neural correlates of specific insight dimensions in enduring schizophrenia and instead have relied on single-item measures of insight. Therefore, the purpose of this study was to examine the association of cortical thickness with the insight dimension of awareness of illness, in a large sample of enduring schizophrenia patients, using a whole-brain approach. We hypothesized that compared to patients with intact insight, patients with impaired insight would have thinner cortex in a network of brain structures associated with self-reflectiveness and metacognition in the temporal, and medial frontal regions. Methods: We used a categorical approach to insight and classified a group of 110 enduring schizophrenia patients in 2 groups according to their summed scores on 3 items of the Scale to Assess Insight (Expanded), which assess awareness of illness. Forty-one patients were classified as having impaired insight into illness (score of 0–5), and 69 patients as intact insight (score >6). T1-weighted structural images were acquired on a 3T MRI scanner for the 2 patient subgroups, and for 69 healthy control subjects matched to patients for age and sex. MR images were processed using CIVET (version 2.0) and quality controlled pre- and post-processing. Whole-brain, vertex-wise linear models were applied to evaluate cortical thickness differences between the 2 patient subgroups and controls. All analyses were controlled for age and sex. Results: There was no significant difference in cortical thickness in either hemisphere between the 2 patient subgroups. However, the impaired insight group displayed significantly thinner cortex within the right insula, temporal gyri, and anterior cingulate cortex compared to healthy controls (P < .05, FDR corrected). There was no significant cortical thickness difference between the intact insight group and healthy controls. Conclusion: These results do not replicate previous findings obtained with smaller samples using single-item measures of insight into illness, and instead suggest that insight into illness may not have a clear neuroanatomical basis at the level of the cortex. Poor awareness of illness may instead be a latent symptom, emerging as a result of a combination of schizophrenia-related deficits, that cannot be captured at the level of the brain. Accordingly, the cortical thinning observed in individuals with impaired insight, but not those with intact insight, compared to controls, may suggest that individuals with impaired insight represent a subset of patients with more severe pathology.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.031
GPT teacher head0.312
Teacher spread0.281 · 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
Published2017
Admission routes1
Has abstractyes

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