A Circadian Rhythm in Heart Rate Variability Contributes to the Increased Cardiac Sympathovagal Response to Awakening in the Morning
Bibliographic record
Abstract
Morning hours are associated with a heightened risk of adverse cardiovascular events. Recent evidence suggests that the sleep-wake cycle and endogenous circadian system modulate cardiac function in humans and may contribute to these epidemiological findings. The aim of the present study was to investigate the interaction between circadian and sleep-wake-dependent processes on heart rate variability (HRV). Fifteen diurnally active healthy young adults underwent a 72-h ultradian sleep-wake cycle (USW) procedure (alternating 60-min wake episodes in dim light and 60-min nap opportunities in total darkness) in time isolation. The present study revealed a significant main effect of sleep-wake-dependent and circadian processes on cardiac rhythmicity, as well as a significant interaction between these processes. Turning the lights off was associated with a rapid increase in mean RR interval and cardiac parasympathetic modulation (high-frequency [HF] power), whereas low-frequency (LF) power and sympathovagal balance (LF:HF ratio) were reduced (p ≤ .001). A significant circadian rhythm in mean RR interval and HRV components was observed throughout the wake and nap episodes (p ≤ .001). Sleep-to-wake transitions occurring in the morning were associated with maximal shifts towards sympathetic autonomic activation as compared to those occurring during the rest of the day. Namely, peak LF:HF ratio was observed in the morning, coincidental with peak salivary cortisol levels. These results contribute to our understanding of the observed increase in cardiovascular vulnerability after awakening in the morning.
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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".