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Record W2001996774 · doi:10.1517/14656566.2015.1022531

Transdermal contraception methods: today’s patches and new options on the horizon

2015· review· en· W2001996774 on OpenAlexaboutno aff
Anita L. Nelson

Bibliographic record

VenueExpert Opinion on Pharmacotherapy · 2015
Typereview
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTolerabilityEstrogenFamily planningIntensive care medicineProgestinPopularityDosingTransdermalGynecologyPopulationInternal medicinePharmacologyAdverse effectEnvironmental health

Abstract

fetched live from OpenAlex

INTRODUCTION: The first contraceptive patch with ethinyl estradiol (EE) and norelgestromin in the United States demonstrated that there was a tremendous interest in topical methods, which could provide patient convenience, steady-state hormonal levels and reassurance of ongoing coverage, while maintaining efficacy and good bleeding patterns. Unfortunately, concerns about increased risk of venous thromboembolism (VTE) risk diminished its popularity. Another version in Europe and Canada had slightly lower estrogen doses, but questions were raised about its VTE risk too based on its progestin. To fill that gap, two new contraceptive patches with lower estrogen levels have been developed and extensively tested. AREAS COVERED: This article provides a short overview of the first set of patches followed by discussions of the pharmacokinetics of the two experimental patches as well as the results of their clinical trials, including information about efficacy, bleeding patterns and tolerability. EXPERT OPINION: Given the recent increased use of first tier contraceptive methods (Intrauterine devices and implants), there may be interest in new patches. Price will influence their popularity. However, a new nondaily delivery system with lower estrogen levels will provide an important option to women.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.002

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 head0.262
GPT teacher head0.519
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 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

Citations11
Published2015
Admission routes1
Has abstractyes

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