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Record W4206265417 · doi:10.3390/women2010001

Gynecological Health Concerns in Women with Schizophrenia and Related Disorders: A Narrative Review of Recent Studies

2022· review· en· W4206265417 on OpenAlexaff
Alexandre González-Rodríguez, Mary V. Seeman, Armand Guàrdia, M. Natividad, Marta Marín, Javier Labad, José Antonio Monreal

Bibliographic record

VenueWomen · 2022
Typereview
Languageen
FieldMedicine
TopicEndometriosis Research and Treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicinePsychosocialBreast cancerPopulationComorbidityPsychiatrySchizophrenia (object-oriented programming)Cervical cancerMenopauseGynecologyCancerInternal medicine

Abstract

fetched live from OpenAlex

Sex and age are important factors influencing physical and mental health in schizophrenia. Our goal was to review the recent literature for associations between gynecological conditions and psychotic illness and to propose integrated strategies for their management in order to improve overall health outcomes in women. We addressed the following questions: What are the prevalence and risk factors of gynecological disorders in women with schizophrenia or delusional disorder (DD)? What are the rates of uptake of gynecological cancer screening and mortality in this population? What role does menopause play? We found an increased incidence of breast cancer in women with schizophrenia. Other gynecological comorbidities were less frequent, but the field has been understudied. Low rates of breast and cervical cancer screening characterize women with schizophrenia. Menopause, because of endocrine changes, aging effects, and resultant comorbidity is associated with high rates of aggressive breast cancer in this population. Uterine and ovarian cancers have been less investigated. Psychosocial determinants of health play an important role in cancer survival. The findings lead to the recommendation that primary care, psychiatry, gynecology, oncology, and endocrinology collaborate in early case finding, in research into etiological links, and in improvement of prevention and treatment.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.938
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.098
GPT teacher head0.430
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.

Study designNot applicable
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

Citations7
Published2022
Admission routes1
Has abstractyes

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