Hormone Therapies and Menopause: Where Do We Stand in the Post-WHI Era?
Bibliographic record
Abstract
The WHI study, its premature termination, and controversy over its findings have motivated patientsand physicians alike to seek lower-dose therapies for menopausal symptoms. Substantial data indicate that low-dose ET/EPT is effective in treating osteoporosis, hot flushes, vulvaginal dryness anditching, and sleeping difficulties. Furthermore, low-dose therapies are associated with a decrease inbreast tenderness compared to standard dose therapies. Some risks associated with standard-doseHT diminish with low-dose treatments. Risk of stroke and venous thromboembolism, for example, fall to placebo levels with low-dose therapies. The nebulous effects on breast cancer and colorectalcancer rates, as well as on risk of CHD, point to the need for further study of low-dose therapies. Inlight of suggestions that timing of HT may play a role in a therapy’s efficacy and safety, more study ofperimenopausal and younger postmenopausal patients is warranted. Such therapy should bestarted as close to the onset of menopause as possible. In addition, recent data suggest that hormone therapy should currently be limited to the lowest dose possible for the duration of timeneeded to alleviate menopausal symptoms and should be in accordance with the patient’s medicalhistory and risk status.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".