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Record W1595047851 · doi:10.1159/000209607

Hormone Therapies and Menopause: Where Do We Stand in the Post-WHI Era?

2009· book-chapter· en· W1595047851 on OpenAlexaff
Michelle P. Warren, Kanani Titchen, Meir Steiner

Bibliographic record

VenueKey issues in mental health (Online)/Key issues in mental health (Print) · 2009
Typebook-chapter
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsSickKids FoundationHospital for Sick ChildrenMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsMedicineMenopauseHormone therapyPlaceboOsteoporosisBreast cancerInternal medicineIntensive care medicineGynecologyOncologyCancerAlternative medicinePathology

Abstract

fetched live from OpenAlex

The WHI study, its premature termination, and controversy over its findings have motivated patientsand physicians alike to seek lower-dose therapies for menopausal symptoms. Substantial data indicate that low-dose ET/EPT is effective in treating osteoporosis, hot flushes, vulvaginal dryness anditching, and sleeping difficulties. Furthermore, low-dose therapies are associated with a decrease inbreast tenderness compared to standard dose therapies. Some risks associated with standard-doseHT diminish with low-dose treatments. Risk of stroke and venous thromboembolism, for example, fall to placebo levels with low-dose therapies. The nebulous effects on breast cancer and colorectalcancer rates, as well as on risk of CHD, point to the need for further study of low-dose therapies. Inlight of suggestions that timing of HT may play a role in a therapy’s efficacy and safety, more study ofperimenopausal and younger postmenopausal patients is warranted. Such therapy should bestarted as close to the onset of menopause as possible. In addition, recent data suggest that hormone therapy should currently be limited to the lowest dose possible for the duration of timeneeded to alleviate menopausal symptoms and should be in accordance with the patient’s medicalhistory and risk status.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.840
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.004
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 head0.030
GPT teacher head0.368
Teacher spread0.338 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2009
Admission routes1
Has abstractyes

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