The effect of oral Contraceptive pills and the natural menstrual cYCLe on arterial stiffness and hemodynamICs (CYCLIC)
Bibliographic record
Abstract
BACKGROUND: Over 100 million women currently use oral contraceptive pills (OCPs) worldwide. However, little is known about the effects of OCPs on arterial stiffness and hemodynamics. Furthermore, whether arterial stiffness and hemodynamics vary throughout the natural menstrual cycle remains controversial. Herein, we estimated the effect of the natural menstrual cycle and OCP use on arterial stiffness and hemodynamics. METHODS: Healthy, nonsmoking women, aged 18-30 years, were recruited if they had regular menstrual cycles and never used OCPs (OCP nonuser group), or were using low-dose OCPs for at least 6 months (OCP user group). Using applanation tonometry, three assessments of arterial stiffness and central and peripheral hemodynamics were performed in a randomized order: during the early follicular (days 3-6), late follicular (days 14-16), and luteal (days 22-26) phases. Within group and between group comparisons were performed using general linear models. RESULTS: Sixty women (21.7 ± 2.8 years) were recruited. Compared with OCP nonusers, OCP users had significantly increased aortic and peripheral SBPs during the active OCP use, but not during the inert tablet phase. No differences in arterial stiffness were noted. CONCLUSION: OCP use was associated with significant increases in aortic and peripheral blood pressures, but not with increased arterial stiffness. Given the widespread OCP use, future longitudinal studies are needed to confirm our findings and assess the long-term effect of OCPs on arterial stiffness and hemodynamics.
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 | 0.001 | 0.003 |
| 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".