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Record W1586487586 · doi:10.20452/pamw.1625

Menopausal hormone therapy for the primary prevention of chronic conditions. U.S. Preventive Services Task Force Recommendation Statement

2013· review· en· W1586487586 on OpenAlexafffund
Catherine Kreatsoulas, Sonia S. Anand

Bibliographic record

VenuePolskie Archiwum Medycyny Wewnętrznej · 2013
Typereview
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsMcMaster University
FundersEli Lilly CanadaEli Lilly and Company
KeywordsMedicineHormone replacement therapy (female-to-male)Randomized controlled trialEstrogenHormone therapyStroke (engine)Clinical trialDiseaseMenopauseDementiaIntensive care medicineGynecologyInternal medicinePhysical therapyBreast cancerCancerTestosterone (patch)

Abstract

fetched live from OpenAlex

Since the early 20th century, scientists have been tantalized with the hypothesis that premenopausal health benefits in women can be preserved in postmenopausal women with the supplementation of exogenous hormone replacement therapy (HRT) of estrogen (alone/with progesterone). This hypothesis was shattered when the results of 2 large randomized controlled trials (RCTs), the Heart Estrogen/Progesterone Replacement Study (HERS) and Women's Health Initiative (WHI), reported an increased risk of adverse clinical outcomes including coronary heart disease, thromboembolic events, stroke, dementia, urinary incontinence, gallbladder disease, and breast cancer. However, since the WHI was published, firestorms of critique, controversy, and multiple subgroup analyses have populated the medical literature, predominantly focused around the analysis of the age of women at entry into the trials (hypothesized as an effect modifier) and suggesting lower-dose preparations including using bioidentical hormones. Recently, the U.S. Preventive Services Task Force (USPSTF) along with other professional groups have issued recommendations against the use of HRT to prevent chronic conditions. In this review, we review the most recent evidence, including the long-term follow-up data from RCTs along a multitude of health outcomes.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.962
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
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 head0.067
GPT teacher head0.408
Teacher spread0.340 · 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

Citations26
Published2013
Admission routes2
Has abstractyes

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