A one-year randomized double-blind, multicentre study to evaluate the effects of an oestrogen-reduced, continuous combined hormone replacement therapy preparation containing 1 mg oestradiol valerate and 2 mg dienogest on metabolism in postmenopausal women
Bibliographic record
Abstract
OBJECTIVES: To evaluate the impact of an oestrogen-reduced, continuous combined hormone replacement therapy preparation containing 1 mg oestradiol valerate (1EV) and 2 mg dienogest (2DNG) on metabolism. METHODS: In a randomized double-blind study, 1EV/2DNG was compared with a reference preparation containing 1 mg 17Beta-oestradiol and 0.5 mg norethisterone acetate (E2/NETA). For the primary variable, i.e. the ratio of HDL cholesterol (week 52 to baseline), at least 98 case evaluations were planned. Secondary variables were other lipid parameters, haemostasis factors and carbohydrate metabolism. RESULTS: After 1 year of treatment, the mean HDL cholesterol levels had decreased by 4.5 +/- 14.8% in the 1EV/2DNG group and by 6.1 +/- 13.9% in the E2/NETA group (treatment difference NS). The ratio of HDL cholesterol (week 52 to baseline) was 0.944 for 1EV/2DNG and 0.929 for E2/NETA (geometric means). The primary efficacy variable, the ratio of the geometric means of the two treatments (1EV/2DNG/E2/NETA) was 1.016, with a lower one-sided 95% confidence limit of 0.973, which was clearly above the prespecified non-inferiority bound of 0.85 (p-value < 0.001). HDL2 cholesterol increased by 0.3 +/- 34.4% (1EV/2DNG) and decreased by 6.2 +/- 34.3% (E2/NETA; treatment difference NS); HDL3 cholesterol decreased by 4.4 +/- 19.9% (1EV/2DNG) and 8.2 +/- 17.7% (E2/NETA; treatment difference NS). Changes in the haemostasis and carbohydrate variables were very similar in both treatment groups. CONCLUSION: This study provides evidence that a new oestrogen-reduced HRT preparation containing 1 mg oestradiol valerate and 2 mg dienogest has no major impact on lipid variables. Minimal changes were seen in haemostatic and carbohydrate variables.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".