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Record W2063358381 · doi:10.1586/17474108.1.1.81

Comparing rosiglitazone with ethinylestradiol/cyproterone acetate in the treatment of polycystic ovary syndrome

2006· article· en· W2063358381 on OpenAlexaff
Marie-Hélène Pesant, Jean‐Patrice Baillargeon

Bibliographic record

VenueExpert Review of Obstetrics & Gynecology · 2006
Typearticle
Languageen
FieldMedicine
TopicOvarian function and disorders
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsCyproterone acetateRosiglitazonePolycystic ovaryMedicinehirsutismInsulin resistanceMetabolic syndromeInternal medicineEndocrinologyCyproteroneAcneDiabetes mellitusInsulinHormoneAndrogenDermatology

Abstract

fetched live from OpenAlex

Recently, an important role of insulin resistance has been demonstrated in polycystic ovary syndrome. New treatment strategies have emerged from this association, as well as a will to prevent long-term metabolic complications of the syndrome, namely metabolic syndrome, Type 2 diabetes mellitus and cardiovascular disease. Rosiglitazone, a member of the thiazolidinedione family, appears to efficiently treat oligoanovulation, menstrual irregularity and hirsutism but it might not be the best treatment for acne. By comparison, ethinylestradiol/cyproterone acetate is not only better than rosiglitazone in controlling menstrual irregularity and acne but also appears to be equally effective in alleviating hirsutism, although it is inferior in restoring fertility. As for long-term complications, rosiglitazone appears to treat the metabolic syndrome and prevent insulin resistance, Type 2 diabetes and cardiovascular disease, while no similar benefit is expected with ethinlyestradiol/cyproterone acetate. Both treatments are equally effective in preventing endometrial neoplasia. In summary, both rosiglitazone and ethinlyestradiol/cyproterone acetate are efficient in treating polycystic ovary syndrome, but there might be a significant advantage of rosiglitazone in preventing long-term metabolic complications of the syndrome.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.381
Threshold uncertainty score0.495

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.029
GPT teacher head0.291
Teacher spread0.262 · 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.

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

Citations2
Published2006
Admission routes1
Has abstractyes

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