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Record W2926696917 · doi:10.1097/gme.0000000000001326

The Kronos Early Estrogen Prevention Study (KEEPS): what have we learned?

2019· review· en· W2926696917 on OpenAlexfundno aff
Virginia M. Miller, Frederick Naftolin, Sanjay Asthana, Dennis M. Black, Eliot A. Brinton, Matthew J. Budoff, Marcelle I. Cedars, N. Maritza Dowling, Carey E. Gleason, Howard N. Hodis, Muthuvel Jayachandran, Kejal Kantarci, Rogerio A. Løbo, JoAnn E. Manson, Lubna Pal, Nanette Santoro, Hugh S. Taylor, S. Mitchell Harman

Bibliographic record

VenueMenopause The Journal of The North American Menopause Society · 2019
Typereview
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Institute of Neurological Disorders and StrokeNational Institute on AgingPfizer PharmaceuticalsUniversity of California, San FranciscoNational Institutes of HealthNational Institute of Arthritis and Musculoskeletal and Skin DiseasesAurora FoundationNational Center for Research ResourcesGeorgia Clinical and Translational Science AllianceEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentKowa CompanyBayer HealthCareAmarin CorporationMedicureMayo Foundation for Medical Education and ResearchBrigham and Women's HospitalAmgenNational Heart, Lung, and Blood InstitutePfizerEsperion TherapeuticsAlzheimer's Drug Discovery Foundation
KeywordsMedicineMenopauseEstrogenInternal medicineWomen's Health InitiativePlaceboMoodAdverse effectEndocrinologyRandomized controlled trialHormone therapyPhysiologyCardiologyPostmenopausal womenBreast cancerPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: The Kronos Early Estrogen Prevention Study (KEEPS) was designed to address gaps in understanding the effects of timely menopausal hormone treatments (HT) on cardiovascular health and other effects of menopause after the premature termination of the Women's Health Initiative. METHOD: The KEEPS was a randomized, double-blinded, placebo-controlled trial to test the hypothesis that initiation of HT (oral conjugated equine estrogens [o-CEE] or transdermal 17β-estradiol [t-E2]) in healthy, recently postmenopausal women (n = 727) would slow the progression of atherosclerosis as measured by changes in carotid artery intima-media thickness (CIMT). RESULTS: After 4 years, neither HT affected the rate of increase in CIMT. There was a trend for reduced accumulation of coronary artery calcium with o-CEE. There were no severe adverse effects, including venous thrombosis. Several ancillary studies demonstrated a positive effect on mood with o-CEE, and reduced hot flashes, improved sleep, and maintenance of bone mineral density with both treatments. Sexual function improved with t-E2. There were no significant effects of either treatment on cognition, breast pain, or skin wrinkling. Variants of genes associated with estrogen metabolism influenced the age of menopause and variability in effects of the HT on CIMT. Platelet activation associated with the development of white matter hyperintensities in the brain. CONCLUSIONS: KEEPS and its ancillary studies have supported the value and safety of the use of HT in recently postmenopausal women and provide a perspective for future research to optimize HT and health of postmenopausal women. The KEEPS continuation study continues to pursue these issues.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.071
GPT teacher head0.379
Teacher spread0.308 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations179
Published2019
Admission routes1
Has abstractyes

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