Arterial Hypertension in Women: State of the Art and Knowledge Gaps
Bibliographic record
Abstract
Hypertension is the leading risk factor for cardiovascular disease and premature death among women globally. However, there is a fundamental lack of knowledge regarding the sex-specific pathophysiology of the condition. In addition, risk factors for hypertension and cardiovascular disease unique to women or female sex are insufficiently acknowledged in clinical guidelines. This review summarizes the existing evidence on women and female-specific risk factors and clinical management of hypertension, to identify critical knowledge gaps relevant to research, clinical practice, and women's heart health awareness. Female-specific risk factors relate not only to reproduction, such as the association of gynecological conditions, adverse pregnancy outcomes or menopause with hypertension, but also to the specific roles of women in society and science, such as gender differences in received medical care and the underrepresentation of women in both the science workforce and as participants in research, which contribute to the limited evidence-based, gender- or sex-specific recommendations. A key point is that the development of hypertension starts in young, premenopausal women, often in association with disorders of reproductive organs, and therefore needs to be managed early in life to prevent future cardiovascular disease. Considering the lower blood pressure levels at which cardiovascular disease occurs, thresholds for diagnosis and treatment of hypertension may need to be lower for women.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".