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Record W2462607228

Steady-state pharmacokinetics of conjugated equine estrogens in healthy, postmenopausal women.

2008· article· en· W2462607228 on OpenAlexaff
Philip R. Mayer, Susanna Tse, Mary Sendi, Dale Bourg, Dennis Morrison

Bibliographic record

VenuePubMed · 2008
Typearticle
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsWomen's Health Research Institute
Fundersnot available
KeywordsEstrogenDosingPharmacokineticsMedicineEstroneSteady state (chemistry)Internal medicineEndocrinologyArea under the curvePharmacologyOral administrationChemistry
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the steady-state exposure of conjugated and unconjugated estrogen components following oral administration of conjugated equine estrogens (2 0.625-mg tablets). STUDY DESIGN: A prospective, open-label, single-treatment study conducted at 1 clinical site with 12 healthy, postmenopausal women. Each subject received 7 daily doses of 2 conjugated equine estrogen (0.625-mg) tablets, and blood samples were taken on the last day of dosing for pharmacokinetic analysis of estrogen components. RESULTS: The major estrogen components after estrogen dosing (as determined by steady-state plasma concentration-time curves) were estrone (100 ng x h/mL), equilin (43.1 ng x h/mL) and delta8,9-dehydroestrone (13.6 ng x h/mL). Several 17beta-reduced forms of estrogen also had consistent plasma concentrations during a steady-state dosing interval. Mean t(max) values ranged from 6.2 to 9.0 hours after dosing, and the 24-hour profiles of the various plasma estrogen concentrations at steady state showed limited fluctuations. CONCLUSION: Oral dosing of conjugated equine estrogen at steady state resulted in consistent concentrations of estrogen components during a dosing interval.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.055
GPT teacher head0.311
Teacher spread0.256 · 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 designObservational
Domainnot available
GenreEmpirical

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
Published2008
Admission routes1
Has abstractyes

Explore more

Same venuePubMed→Same topicMenopause: Health Impacts and Treatments→French-language works237,207→