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Record W4393192470 · doi:10.1016/j.psycom.2024.100166

Metabolic syndrome associations with neurocognitive function in first-episode schizophrenia spectrum disorders

2024· article· en· W4393192470 on OpenAlexaboutno aff
Hilmar Luckhoff, Sharain Suliman, Leigh L. van den Heuvel, Retha Smit, Sanja Kilian, Erine Bröcker, Lebogang Phaladira, Laila Asmal, Soraya Seedat, Robin Emsley

Bibliographic record

VenuePsychiatry Research Communications · 2024
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsnot available
FundersSouth African Medical Research CouncilNational Research Foundation
KeywordsNeurocognitiveSchizophrenia spectrumSchizophrenia (object-oriented programming)PsychologyPsychiatryClinical psychologyMedicineCognitionPsychosis

Abstract

fetched live from OpenAlex

We examined the associations between metabolic syndrome (MetS) and neurocognitive function in patients with first-episode schizophrenia spectrum disorders (FES) compared to controls assessed using the Repeatable Battery for the Assessment of Neuropsychological Status. In patients, psychopathology was assessed using the Positive and Negative Syndrome Scale and Calgary Depression Scale for Schizophrenia. First, we found illness- and domain-specific associations between the individual MetS features and neurocognitive performance in patients, but not in controls. Second, body mass index and total cholesterol levels were lower in patients than controls, which in turn correlated with increased global psychopathology severity and cognitive deficits. Third, negative symptoms moderated the association between low HDL cholesterol and poorer immediate verbal memory performance in patients. Our findings suggest that distinct lipid profile alterations are associated with cognitive performance and psychopathology severity in patients with FES. Further studies are needed to explore the associations of MetS with neurocognition over time, as well as how these relationships are affected by socio-demographic and clinical factors, including depression, anxiety, and related psychopathology.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.401
Threshold uncertainty score0.935

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.001

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 head0.045
GPT teacher head0.358
Teacher spread0.313 · 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.

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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