Coronary artery disease in post-menopausal women: are there appropriate means of assessment?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The recognition of sex differences in cardiovascular disease, particularly the manifestations of coronary artery disease (CAD) in post-menopausal women, has introduced new challenges in not only understanding disease mechanisms but also identifying appropriate clinical means of assessing the efficacy of management strategies. For example, the majority of treatment algorithms for CAD are derived from the study of males, focus on epicardial stenoses, and inadequately account for the small intramyocardial vessel disease in women. However, newer investigational modalities, including stress perfusion cardiac magnetic resonance imaging and positron emission tomography are providing enhanced diagnostic accuracy and prognostication for women with microvascular disease. Moreover, these investigations may soon be complemented by simpler screening tools such as retinal vasculature imaging, as well as novel biomarkers (e.g. heat shock protein 27). Hence, it is vital that robust, sex-specific cardiovascular imaging modalities and biomarkers continue to be developed and are incorporated into practice guidelines that are used to manage women with CAD, as well as gauge the efficacy of any new treatment modalities. This review provides an overview of some of the sex differences in CAD and highlights emerging advances in the investigation of CAD in post-menopausal 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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it