Association of novel EEG biomarkers of sleep depth and cortical arousability with cardiac autonomic modulation in adolescents
Bibliographic record
Abstract
STUDY OBJECTIVES: To examine the developmental association of the odds ratio product (ORP), an electroencephalographic measure of sleep depth, during non-rapid eye movement (NREM) sleep with 24-hour heart rate variability (HRV), an electrocardiographic measure of cardiac autonomic modulation (CAM), in the transition to adolescence. METHODS: Leveraging data from the Penn State Child Cohort, we performed longitudinal analyses on 313 children (median [Md] age 9 years) followed-up after Md = 7.4y and cross-sectional analyses on 344 adolescents (Md = 16 years). We extracted ORP during NREM sleep and in the 9 seconds following cortical arousals (ORP-9) from 9-hour, in-lab polysomnography, and frequency- and time-domain HRV indices from 24-hour Holter ECG monitoring. Longitudinal and cross-sectional, multivariable-adjusted, regression models examined the association between ORP and ORP-9 with adolescent 24-hour HRV indices. RESULTS: Longitudinally, a greater increase in ORP-9 since childhood was associated with lower daytime Log-LF, SDNN, RMSSD, and higher HR in adolescence (p < .05). A greater increase in ORP since childhood was associated with lower nighttime Log-LF and SDNN (p < .05). Cross-sectionally, higher ORP and ORP-9 were associated with lower daytime and nighttime Log-LF, SDNN or RMSSD and higher HR within adolescence (p < .05). CONCLUSIONS: A greater increase in cortical arousability since childhood is a strong developmental predictor of daytime cardiac autonomic imbalance in adolescence. Shallower sleep depth additionally arises as a proximal determinant of both daytime and nighttime cardiac autonomic imbalance within adolescence. These data suggest a coupling between fine-grained spectral measures of the sleeping brain and those of CAM, which may inform sleep-related cardiovascular risk early in life.
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 | 0.000 | 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".