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Record W2273761161 · doi:10.1017/s1092852900025499

Metabolic and Endocrine Disturbances in Psychiatric Disorders: A Multidisciplinary Approach to Appropriate Atypical Antipsychotic Utilization

2005· article· en· W2273761161 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCNS Spectrums · 2005
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsAstraZeneca (Canada)
Fundersnot available
KeywordsMedicineDyslipidemiaDiabetes mellitusMetabolic syndromeAntipsychoticEndocrine systemDiabetic ketoacidosisBody mass indexPsychiatryKetoacidosisAtypical antipsychoticPopulationPediatricsInternal medicineEndocrinologySchizophrenia (object-oriented programming)HormoneType 1 diabetes

Abstract

fetched live from OpenAlex

Patients with psychiatric disorders have an increased rate of cardiovascular morbidity and mortality compared with the general population. Metabolic issues such as weight gain, dyslipidemia, diabetes mellitus, diabetic ketoacidosis,and pancreatitis have been reported with the use of antipsychotic agents. Although atypical antipsychotics have not been linked directly to the development of metabolic syndrome, these medications have been shown to increase risk factors that can lead to metabolic and endocrine disturbances. Therefore, clinicians should provide ongoing monitoring for patients who are being treated for psychiatric disorders with these agents. According to the 2004 Consensus Report on Antipsychotics, screening measures should include baseline and follow-up monitoring of personal/family histories, weight (body mass index), waist circumference, blood pressure, fasting plasma glucose, and fasting lipid profile.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.370
Threshold uncertainty score0.617

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.027
GPT teacher head0.316
Teacher spread0.290 · 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