Oral Contraceptive Pill Phase Does Not Influence Heart Rate Variability, Measured Using The Oura® Ring.
Bibliographic record
Abstract
Heart rate variability (HRV) is the shift in timing between successive heart cycles and has been shown to be an indicator of overall health. Some research has found that HRV increases from the follicular to the luteal phase of the menstrual cycle, however these findings are not universal, and limited studies investigate the oral contraceptive pill (OCP) cycle. Moreover, all the current studies investigating the influence of hormonal cycle phase on HRV use in-lab techniques, such as research grade electrocardiogram monitoring. The OURA® smart ring allows for assessment of an index of HRV in free living situations. PURPOSE: To investigate the influence of OCP phase on HRV, measured using the OURA® smart ring. METHODS: This study included 14 premenopausal females using a second generation OCP, who wore the OURA® smart ring during both the active (days 14-21) and placebo (21-28) weeks of the OCP cycle. Root mean square of successive differences in heart rate was calculated from the OURA® smart ring nocturnal heart rate data using the 250 Hz infrared photoplethysmography, and the average across each cycle phase (3-5 days) was used. Data were analyzed using a Welch’s t-test, and all data are reported as mean ± SD, with α criterion set to 0.05. RESULTS: No difference in HRV was observed between the phases of the OCP cycle (Active: 63.4 ± 21.2 ms, Placebo: 67.8 ± 21.2 ms, p = 0.59, d = 0.21). CONCLUSION: These findings suggest no influence of OCP phase on HRV in young, healthy females. Future research should focus on the potential regulatory mechanisms by which estrogen and progesterone could influence autonomic function. Additionally, robust assessment of the validity and reliability of wearable HRV monitoring systems, such as the OURA® smart ring, must be conducted. Supported by: Natural Sciences and Engineering Research Council of Canada
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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 | 0.003 |
| 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) | 0.003 | 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".