Unique cardiometabolic factors in women that contribute to modified cardiovascular disease risk
Bibliographic record
Abstract
Major risk factors of cardiovascular disease (CVD) include hypertension, obesity, diabetes mellitus and metabolic syndrome; all of which are considered inflammatory conditions. Women are disproportionately affected by inflammatory conditions, with sex differences emerging as early as adolescence. Hormonal fluctuations associated with reproductive events such as menarche, pregnancy and menopause, are hypothesized to promote a pro-inflammatory state in women. Moreover, women who have experienced inflammatory-type conditions such as polycystic ovarian syndrome (PCOS), gestational diabetes or pre-eclampsia, have a cardiometabolic phenotype that pre-disposes to increased risk of myocardial infarction, stroke and coronary heart disease. Women with no notable CVD risk factors are often relatively protected from CVD pre-menopause; but overtake men in risk of major cardiovascular events when the cardiovascular protective effects of oestrogen begin to wane. Sex differences and female-specific factors have long been considered challenging to study and this has led to an underrepresentation of females in clinical trials and lack of female-specific data from pre-clinical studies. However, there is now a clear prerogative to include females at all stages of research, despite inherent complexities and potential variability in data. This review explores recent advancements in our understanding of CVD in women. We summarise the underlying factors unique to women that can promote CVD risk factors, ultimately contributing to CVD burden and the emerging therapies aimed to combat this.
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 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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".