Strategies and methods to study female-specific cardiovascular health and disease: a guide for clinical scientists
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: In 2001, the Institute of Medicine's (IOM) report, "Exploring the Biological Contributions to Human Health: Does Sex Matter?" advocated for better understanding of the differences in human diseases between the sexes, with translation of these differences into clinical practice. Sex differences are well documented in the prevalence of cardiovascular (CV) risk factors, the clinical manifestation and incidence of cardiovascular disease (CVD), and the impact of risk factors on outcomes. There are also physiologic and psychosocial factors unique to women that may affect CVD risk, such as issues related to reproduction. METHODS: The Society for Women's Health Research (SWHR) CV Network compiled an inventory of sex-specific strategies and methods for the study of women and CV health and disease across the lifespan. References for methods and strategy details are provided to gather and evaluate this information. Some items comprise robust measures; others are in development. RESULTS: To address female-specific CV health and disease in population, physiology, and clinical trial research, data should be collected on reproductive history, psychosocial variables, and other factors that disproportionately affect CVD in women. Variables related to reproductive health include the following: age of menarche, menstrual cycle regularity, hormone levels, oral contraceptive use, pregnancy history/complications, polycystic ovary syndrome (PCOS) components, menopause age, and use and type of menopausal hormone therapy. Other factors that differentially affect women's CV risk include diabetes mellitus, autoimmune inflammatory disease, and autonomic vasomotor control. Sex differences in aging as well as psychosocial variables such as depression and stress should also be considered. Women are frequently not included/enrolled in mixed-sex CVD studies; when they are included, information on these variables is generally not collected. These omissions limit the ability to determine the role of sex-specific contributors to CV health and disease. Lack of sex-specific knowledge contributes to the CVD health disparities that women face. CONCLUSIONS: The purpose of this review is to encourage investigators to consider ways to increase the usefulness of physiological and psychosocial data obtained from clinical populations, in an effort to improve the understanding of sex differences in clinical CVD research and health-care delivery for women and men.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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