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Record W2789361954 · doi:10.1097/yco.0000000000000410

Use of psychotropic medication in women with psychotic disorders at menopause and beyond

2018· review· en· W2789361954 on OpenAlexaff
Mary V. Seeman, Alexandre González-Rodríguez

Bibliographic record

VenueCurrent Opinion in Psychiatry · 2018
Typereview
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMenopausePsychotropic medicationPsychiatryMedicinePsychologyClinical psychologyMental healthInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Drugs have been extensively prescribed for the treatment of psychotic symptoms in schizophrenia and related disorders, as well as for the management of psychotic features in delirium, dementia and affective disorders. The aim of this narrative review is to focus on the recent literature on drug treatment in women with psychosis at the transition to menopause and subsequently. RECENT FINDINGS: The recent literature emphasizes the following points: the efficacy of antipsychotic medication in psychosis is largely confined to the alleviation of delusions and hallucinations; menopause and ageing alter the kinetics and dynamics of drug action; drugs other than antipsychotics are currently being tested to address the cognitive, affective and negative symptoms of psychotic illnesses; menopausal symptoms add to comorbidities and require simultaneous treatment, raising the probability of deleterious drug interactions; antipsychotic drugs have many side effects and contribute to high mortality rates in the older psychosis population. SUMMARY: A major implication for research is that antipsychotic drugs with a wider range of action and with fewer side effects are urgently needed. The clinical implications of the pharmacotherapy of psychotic illness are: older women's needs must be assessed through a comprehensive history and review of systems and physical and mental examination. To avoid adverse effects, drug dosages are best kept low and polypharmacy avoided wherever possible. It is important to frequently reassess older patients, as their pharmacotherapy requirements change with age and with comorbidity.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.920
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.066
GPT teacher head0.392
Teacher spread0.326 · 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.

Study designOther design
Domainnot available
GenreReview

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
Published2018
Admission routes1
Has abstractyes

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