Abstract 342: Perimenopausal Transdermal Estrogen Replacement Therapy Reduces Serum High-density Lipoprotein Cholesterol Efflux Capacity but Improves Cardiovascular Risk Factors
Bibliographic record
Abstract
Background: The cardiovascular (CV) safety of estrogen replacement therapy (ERT) in perimenopausal women remains uncertain, as do the effects of ERT on high-density lipoprotein (HDL). Although exogenous estrogens increase HDL cholesterol (HDL-C), estrogen-mediated effects on alternative metrics of HDL that better predict CV risk are unknown. Objective: To determine the effects of transdermal ERT on HDL particle concentration, protein composition, and cholesterol efflux capacity (CEC), as well as the relationships between these metrics and CV risk factors. Methods: Fasting plasma samples were analyzed from 101 healthy, normolipidemic perimenopausal women enrolled in the Perimenopausal Estrogen Replacement Therapy study. Subjects were randomized to receive either transdermal placebo or transdermal estradiol (100 μg/24 hr) with cyclic micronized progesterone for 12 months. At baseline and after 6 months of treatment, serum HDL CEC, HDL particle concentration, HDL protein composition, insulin resistance and brachial artery flow-mediated dilatation (FMD) were measured. Results: No difference between groups was found for change in plasma concentration of HDL-C (-1.5±6.9 mg/dL in the ERT group vs. -0.8±8.9 mg/dL in the placebo group, p=0.69). However, significant between-group differences were found for changes in serum HDL total CEC (-0.45±2.5% in the ERT group vs. +0.37±1.1% in the placebo group, p=0.02) and ABCA1-specific CEC (-0.39±1.8% in the ERT group vs. +0.81±1.5% in the placebo group). Change in total HDL particle concentration did not differ between groups (p=0.90). Relative to placebo, transdermal ERT led to reductions in low-density lipoprotein cholesterol (-13±18 mg/dL in the ERT group vs. +4.3±17 in the placebo group, p<0.0001) and insulin resistance (mean change in HOMA-IR -0.66±1.2 in the ERT group vs. +0.26±1.1 in the placebo group, p=0.0002). An inverse correlation was found between changes in serum HDL total CEC and FMD (β=-0.26, p=0.004). Conclusions: Natural menopause leads to an increase in serum HDL CEC, an effect that is abrogated by transdermal ERT. However, transdermal ERT leads to favorable changes in major CV risk factors, suggesting that change in HDL CEC is not a reliable metric of CV risk in perimenopausal women.
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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 | 0.000 | 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) | 0.004 | 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".