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Record W4411048817 · doi:10.1016/j.jogoh.2025.102983

The “Women’s Heart Bus”: the first french initiative for the prevention of cardiovascular and gynaecological risk in women, prospective multicentre analysis of 4,300 participants

2025· article· en· W4411048817 on OpenAlexfundno aff
M. Jouffroy, Patrick Devos, Thierry Drilhon, Claire Mounier‐Véhier

Bibliographic record

VenueJournal of Gynecology Obstetrics and Human Reproduction · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Issues in Pregnancy
Canadian institutionsnot available
FundersPfizer FranceFonds de Recherche du Québec - SantéBoehringer Ingelheim France
KeywordsMedicineGynecology

Abstract

fetched live from OpenAlex

OBJECTIVE: To assess the cardiovascular and gynaecological health status of women in France, based on data collected through the Women's Heart Bus screening and prevention campaign. METHODS: A mobile screening campaign was carried out in 20 cities across France between September 2021 and November 2022. The initiative aimed to establish the cohort of the National Women's Health Observatory (ONSF) and included 4300 women. A structured assessment booklet was used to collect information on cardiovascular, metabolic, and gynaecological-obstetric risk factors, as well as on medical follow-up by general practitioners and cardiologists. Gynaecological screening practices were also analysed in relation to age and national screening guidelines. RESULTS: Among the women included, 90.2 % had at least two cardiovascular or metabolic risk factors, and 48.9 % had two or more gynaecological-obstetric risk factors. More than 70 % had never received cardiovascular follow-up, and fewer than half were up to date with gynaecological screening. CONCLUSION: The findings underscore the urgent need to improve cardiovascular and gynaecological health in women in France. The Women's Heart Bus enabled many women to be reintegrated into appropriate care pathways.

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)0.004
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.164
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.013
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 head0.023
GPT teacher head0.298
Teacher spread0.275 · 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.

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

Citations1
Published2025
Admission routes1
Has abstractyes

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