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Record W4412156841 · doi:10.1080/09513590.2025.2526560

Targeting vasomotor symptoms with the new drug fezolinetant – an expert overview

2025· review· en· W4412156841 on OpenAlexfundno aff
Rossella E. Nappi, Angelo Cagnacci, Costantino Di Carlo, Alessandro D. Genazzani, Paola Villa, Tommaso Simoncini

Bibliographic record

VenueGynecological Endocrinology · 2025
Typereview
Languageen
FieldMedicine
TopicHormonal and reproductive studies
Canadian institutionsnot available
FundersAstellas Foundation for Research on Metabolic DisordersAstellas PharmaAstellas Pharma Canada
KeywordsVasomotorDrugMedicinePharmacologyIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Menopause is an inevitable event in the life of women who live long enough to reach this milestone. The experience of menopause varies amongst individuals. Menopause has a negative impact on women's life and is associated with symptoms including vasomotor symptoms (VMS), such as hot flushes and night sweats, sleep disturbances and low mood. VMS are bothersome and may have a long duration. Menopause hormone therapy (MHT) is recommended in women with symptoms; however, its use is limited. The recent approval of fezolinetant offers a new therapeutic option for women who suffer from VMS and are unsuitable or averse to MHT. Fezolinetant is a precision drug as it targets the pathological mechanism of VMS showing some effect also on sleep disturbances. Given how variable the experience of menopause is, it is important to offer individualized treatment options to women who suffer from menopause-related symptoms and let them be part of the shared decision making.

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 score0.004
Threshold uncertainty score0.014

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 studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.049
GPT teacher head0.354
Teacher spread0.305 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

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