Heart rate variability as a function of menopausal status, menstrual cycle phase, and estradiol level
Bibliographic record
Abstract
Abstract Low estradiol status is associated with increased cardiovascular risk. We sought to determine the association between heart rate variability (HRV), a marker of cardiovascular risk, at baseline and in response to stressor as a function of menopausal status, menstrual cycle phase and estradiol level. Forty‐one healthy women (13 postmenopausal, 28 premenopausal) were studied. Eleven premenopausal women were additionally studied in the high and low estradiol phases of the menstrual cycle. HRV was calculated by spectral power analysis (low Frequency (LF), high frequency (HF) and LF:HF) at baseline and in response to graded Angiotensin II (AngII) infusion. The primary outcomes were differences in HRV at baseline and in response to AngII. Compared to premenopausal women in the low estradiol phase, postmenopausal women demonstrated lower baseline LF ( p = 0.01) and HF ( p < 0.001) measures, which were not significant after adjustment for age and BMI. In response to AngII, a decrease in cardioprotective HRV (ΔHF = −0.43 ± 0.46 ln ms 2 , p = 0.005 vs. baseline) was observed in postmenopausal women versus premenopausal women. Baseline HRV parameters did not differ by menstrual phase in premenopausal women. During the low estradiol phase, no differences were observed in the HRV response to AngII challenge. In contrast, women in the high estradiol phase were unable to maintain HRV (ΔLF = −0.07 ± 0.46 ln ms 2 , p = 0.048 response vs. baseline, ΔHF = −0.33 ± 0.74 ln ms2, p = 0.048 response vs. baseline). No association was observed between any measure of HRV and estradiol level. Menopausal status and the high estradiol phase in premenopausal women were associated with reduced HRV, a marker of cardiovascular risk. Understanding the role of estradiol in the modulation of cardiac autonomic tone may help guide risk reduction strategies in 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 | 0.001 |
| 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) | 0.001 | 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".