Effects of combined 17β-estradiol and progesterone on weight and blood pressure in postmenopausal women of the REPLENISH trial
Bibliographic record
Abstract
OBJECTIVE: To examine the impact of a single-capsule 17β-estradiol (E2)/progesterone (P4) on weight and blood pressure (BP) when treating moderate to severe vasomotor symptoms in postmenopausal women with a uterus. METHODS: Healthy postmenopausal women with a uterus (aged 40-65, body mass index ≤34 kg/m2, BP ≤140/90 mm Hg) were randomized to daily E2/P4 (mg/mg; 1/100, 0.5/100, 0.5/50, 0.25/50) or placebo in the phase 3 REPLENISH trial (NCT01942668). Changes in weight and BP from baseline to month 12 were evaluated. Potentially clinically important changes were defined as increases or decreases from baseline in weight by ≥15% and ≥11.3 kg, systolic BP by ≥20 mm Hg (absolute value ≥160 or ≤90 mm Hg), and diastolic BP by ≥15 mm Hg (absolute value ≥90 or ≤60 mm Hg). RESULTS: Overall mean changes in weight and BP from baseline to month 12 with E2/P4 were modest and generally not statistically or clinically significant versus placebo. Incidence of potentially clinically important changes was low for weight (E2/P4 vs placebo: 1.1-2.6% vs 2.2%), systolic BP (0.3-1.1% vs 1.1%), and diastolic BP (1.4-4.2% vs 3.2%). A small number of women had treatment-related, treatment-emergent adverse events of weight gain (1.4-2.6% vs 1.3%) or hypertension (0.2-1.2% vs 0%). Few women who discontinued E2/P4 had weight gain (1.6%) or hypertension (0.6%) as a primary reason. Efficacy profile on VMS was consistent with previous findings and not modified by body mass index. CONCLUSIONS: Twelve-month use of E2/P4 had no clinically meaningful impact on weight or BP in postmenopausal women of the REPLENISH study.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".