Short-term stability of resting heart rate variability: influence of position and gender
Bibliographic record
Abstract
Heart rate variability (HRV) is utilized within laboratory and clinical settings as a noninvasive indicator of cardiac autonomic modulation. Past research has utilized a wide variety of resting methodologies and, as such, it is difficult to draw conclusions on the nature of HRV from different studies. Therefore, the current study aimed to assess the short-term stability of resting HRV during a 40-min resting trial and the impact of body position and gender on this short-term stability. Resting HRV was determined from 40-min trials in 3 standard positions (supine, seated, and standing) for healthy males (n = 14) and females (n = 16). Time-domain, geometric, and frequency-domain measures of resting HRV were examined during consecutive 10-min segments using a 3-way ANOVA (time × position × gender) and Tukeys' post-hoc tests with reproducibility assessed by intraclass correlation coefficients (ICC) and coefficients of variation. During rest, most HRV measures fluctuated over time, were greater in the supine compared to the standing position, and were greater for males compared with females. Variables that reflected primarily vagal modulations of heart rate remained stable, whereas other HRV measures varied over time. The majority of HRV variables exhibited substantial to excellent short-term reproducibility (ICC > 0.6) with time-domain and geometric measures of HRV demonstrating greater values compared with frequency-domain parameters. Based on the current results, the recording and analysis of HRV at 0-10 min of rest was recommended as a standardized protocol for the assessment of resting HRV in any standard position for either gender during laboratory and (or) clinical settings.
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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 | 0.001 | 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".