1 and 2 mg 17β-estradiol combined with sequential dydrogesterone have similar effects on the serum lipid profile of postmenopausal women
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to assess the effects of 1 and 2 mg 17beta-estradiol on serum lipid profile. Beneficial effects have been clearly established in previous studies with a 2 mg dose; further evidence was required to confirm the beneficial effects of a 1 mg dose. METHODS: This double-blind, placebo-controlled study involved 579 postmenopausal women randomized to oral treatment with placebo, 1 mg/day 17beta-estradiol sequentially combined with 5 or 10 mg/day dydrogesterone for the last 14 days of each 28-day cycle, or 2 mg/day 17beta-estradiol sequentially combined with 10 or 20 mg/day dydrogesterone for the last 14 days of each 28-day cycle. Treatment was continued for 26 cycles. RESULTS: High density lipoprotein (HDL) cholesterol levels were significantly (p<0.05) increased after 26 cycles in all active treatment groups compared with placebo. In addition, low density lipoprotein (LDL) cholesterol and lipoprotein(a) levels were significantly reduced, and apolipoprotein A1 and triglyceride levels were significantly increased, in all active treatment groups after 13 and 26 cycles. CONCLUSIONS: The results of this study clearly indicate that sequential combinations of either 1 or 2 mg 17beta-estradiol with dydrogesterone are associated with long-term, favorable changes in the serum lipid profile. There was no evidence that dydrogesterone compromised the 17beta-estradiol-induced improvements in lipid profile.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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