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Record W1927857238 · doi:10.1017/s109285290002318x

Treatment of Menopause-Related Mood Disturbances

2005· review· en· W1927857238 on OpenAlexaffabout
Cláudio N. Soares, Jennifer Prouty, L. Ingeborgh van den Born, Meir Steiner

Bibliographic record

VenueCNS Spectrums · 2005
Typereview
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMenopauseMoodMedicineHormone therapyVasomotorDepression (economics)OsteoporosisEstrogenDiseaseSexual dysfunctionCognitive declinePsychiatryGerontologyGynecologyInternal medicineBreast cancerDementiaCancer

Abstract

fetched live from OpenAlex

More than 1.7 million American women are expected to reach menopause each year. Recent Canadian statistics show that a 50-year-old woman can now expect to live until her mid-80s, which implies living at least one-third of her life after menopause. The menopausal transition is typically marked by intense hormonal fluctuations, accompanied by vasomotor symptoms (eg, hot flashes, night sweats), sleeps disturbance, and changes in sexual function, as well as increased risk for osteoporosis, cardiovascular disease, and cognitive decline. More importantly, recent studies have demonstrated a significant association between menopausal transition and a higher risk for developing depression. In the post-Women's Health Initiative Study era, physicians and patients are questioning the safety and efficacy of long-term hormone therapy use. This article reviews the current literature on the benefits and risks of using hormone therapy for the treatment of menopause-related mood disturbances and alternate strategies currently available for the management of menopause-related problems, including antidepressants, complementary and alternative medicine, and selective estrogen receptor modulators.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.061
GPT teacher head0.380
Teacher spread0.318 · 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

Citations21
Published2005
Admission routes2
Has abstractyes

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