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Record W4414978017 · doi:10.1177/30494826251383849

Valvular Heart Diseases in Women: Where Are We Now?

2025· article· en· W4414978017 on OpenAlexafffund
Kathia Abdoun, Paolo Springhetti, Andréanne Powers, Marie‐Annick Clavel

Bibliographic record

VenueJournal of the Heart Valve Society · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsUniversité LavalInstitut universitaire de cardiologie et de pneumologie de Québec
FundersInstitute of Circulatory and Respiratory Health
KeywordsHealthcare systemHealth carevalvular heart diseaseHeart failureMEDLINEDisease

Abstract

fetched live from OpenAlex

Valvular heart diseases (VHDs) pose significant challenges to cardiovascular health globally, contributing substantially to morbidity and mortality. Despite advancements in therapeutic strategies, women frequently face delayed diagnoses, surgical referrals, and encounter poorer postoperative results compared to men. This inequity stems from historical biases where women were underrepresented in pivotal studies shaping current medical guidelines. However, emergent research focuses more frequently on women, highlighting remarkably sex-differences in VHD etiology, diagnosis, and treatment. Acknowledging and addressing these differences is required for fair healthcare and optimized clinical outcomes for both sexes in the current era. Hence, this review proposes to highlight the implications of sex-differences concerning diagnosis, treatment modalities, and outcomes among patients affected by VHDs.

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)0.005
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
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
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 head0.011
GPT teacher head0.328
Teacher spread0.317 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

Explore more

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