The effect of endogenous estrogen on Doppler-estimated right ventricular systolic pressure during exercise
Bibliographic record
Abstract
We evaluated the effect of endogenous estrogen levels on exercise-related changes in right ventricular systolic pressure (RVSP) of healthy, eumenorrheic, sedentary women. Volunteers were studied at two separates phases of the menstrual cycle (LO and HI estrogen phases), exercised on a semi-supine ergometer with escalating workload and monitored continuously by 12-lead ECG and automated blood pressure cuff. At each exercise stage, Doppler echocardiography measurements were obtained and analyzed to determine RVSP. Fourteen subjects (age 24 ± 5) were studied. Exercise duration was significantly higher on the HI estrogen day, but no significant differences in hemodynamic response to exercise were found between the two study days. There were also no significant differences with respect to heart rate (HR) acceleration during early exercise, as well as resting and peak RVSP, HR, blood pressure, and rate pressure product. Doppler-estimated RVSP demonstrated a linear relationship to HR at a ratio of 1 mm Hg (1 mm Hg = 133.3224 Pa) for every 5 bpm (beats per minute) increase in HR. There were no differences in the slope of this relationship between HI and LO estrogen phases of the menstrual cycle. Our findings did not demonstrate any effect of endogenous estrogen levels on the modulation of the pulmonary vascular response to exercise in healthy women.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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".