Pulse rate variability in children with disordered breathing during different sleep stages
Bibliographic record
Abstract
Heart Rate Variability (HRV), the variation of time intervals between heartbeats, is an indirect and noninvasive method for monitoring the autonomic activities that control heart rate. Traditionally, HRV is measured from the electrocardiogram. In this study, we estimated HRV from the photoplethysmogram (PPG), called pulse rate variability (PRV) and investigated the effects of sleep disordered breathing (SDB) and different sleep stages on it. We recorded the overnight PPG signals from 160 children using the Phone Oximeter, an oximeter connected to a mobile phone, simultaneously with the other signals within standard polysomnography. We analysed the mean pulse-to-pulse intervals, the power of low (LF) and high frequency (HF) bands of PRV and also the ratio of LF power to HF power (LF/HF) in the children with SDB during non-rapid eye movement (non-REM) and rapid eye movement (REM) sleep. The results showed that the normalized LF increased in children with SDB (from 0.26±0.12 to 0.29±0.13 during non-REM sleep and from 0.37±0.12 to 0.40±0.15 during REM sleep), the LF/HF ratio increased in children with SDB (from 0.67±0.55 to 1.05±1.00 in non-REM sleep and from 1.46±2.20 to 1.74±1.38 in REM) and the HF components decreased in children with SDB (from 0.61±0.16 to 0.55±0.17 in non-REM sleep and from 0.47±0.14 to 0.43±0.16 in REM sleep). The results may confirm the pronounced sympathetic and the diminished parasympathetic activity in children with SDB. This study indicates that PRV obtained from the PPG reflects the autonomic regulation of heart rate in disordered breathing during different sleep stages.
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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 | 0.002 |
| 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".