Why We Need Specialised Centres for Women’s Hearts: Changing the Face of Cardiovascular Care for Women
Bibliographic record
Abstract
Although cardiovascular disease (CVD) is the leading cause of mortality in women globally, cardiovascular care for women remains suboptimal, with poorer outcomes than for men. During the past two decades, there has been an incremental increase in research and publications on CVD in women, addressing sex-specific risk factors, symptoms, pathophysiology, treatment, prevention and identification of inequities in care. Nonetheless, once women have manifested CVD, they continue to have increasingly worse outcomes than men. An approach to addressing these global disparities has been the worldwide establishment of specialised centres providing cardiovascular care for women. These women's heart centres (WHCs) allow a comprehensive approach to the cardiovascular care of women across the lifespan. The purpose of this article is to define the need for and role of these specialised centres by outlining sex-specific gaps in CVD care, and to provide guidance on components within WHCs that may be considered when establishing such programmes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".