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Record W1991705675 · doi:10.9758/cpn.2012.10.1.1

Are Cardiometabolic and Endocrine Abnormalities Linked to Sleep Difficulties in Schizophrenia? A Hypothesis Driven Review

2012· article· en· W1991705675 on OpenAlexaff
Rébecca Robillard, Naomi L. Rogers, Bradley Whitwell, Tim Lambert

Bibliographic record

VenueClinical Psychopharmacology and Neuroscience · 2012
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsSchizophrenia (object-oriented programming)Sleep disorderMedicinePsychiatryBody mass indexPsychosisObesityPsychologyCognitionClinical psychologyInternal medicine

Abstract

fetched live from OpenAlex

Schizophrenia is a psychiatric disorder that includes symptoms such as hallucinations, disordered thoughts, disorganized or catatonic behaviour, cognitive dysfunction and sleep-wake disturbance. In addition to these symptoms, cardiometabolic dysfunction is common in patients with schizophrenia. While previously it has been thought that cardiometabolic symptoms in patients with schizophrenia were associated with medications used to manage this disorder, more recently it has been demonstrated that these symptoms are present in drug naive and unmedicated patients. Sleep-wake disturbance, resulting in chronic sleep loss has also been demonstrated to induce changes in cardiometabolic function. Chronic sleep loss has been associated with an increased risk for weight gain, obesity and cardiac and metabolic disorders, independent of other potentially contributing factors, such as smoking and body mass index. We hypothesise that the sleep-wake disturbance comorbid with schizophrenia may play a significant role in the high prevalence of cardiometabolic dysfunction observed in this patient population. Here we present a critical review of the evidence that supports this hypothesis.

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)0.001
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 score0.120
Threshold uncertainty score0.797

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.070
GPT teacher head0.403
Teacher spread0.333 · 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

Citations10
Published2012
Admission routes1
Has abstractyes

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