Unique Aspects of Women's Valvular Heart Diseases: Impact for Diagnosis and Treatment
Bibliographic record
Abstract
Valvular heart diseases (VHDs) are a major cause of cardiovascular morbidity and mortality worldwide. As degenerative and functional mechanisms represent the main etiologies in high-income countries are degenerative and functional, while in low income countries etiologie is mostly rheumatic. Although therapeutic options have evolved considerably in recent years, women are consistently diagnosed at later stages of their disease, are delayed in receiving surgical referrals, and exhibit worse postoperative outcomes, compared to men. This difference is a result of the historical underrepresentation of women in studies from which current guidelines were developed. However, in recent years, important research, including more female patients, has been conducted and has highlighted substantial sex-specific differences in the etiology, diagnosis, and treatment of VHDs. Systematic consideration of these sex-specific differences in VHD patients is crucial for providing equitable healthcare and optimizing clinical outcomes in both female and male patients. Hence, this review aims to explore implications of sex-specific particularities for diagnosis, treatment options, and outcomes in women with VHDs.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".