Heart rate variability analysis in comorbid insomnia and sleep apnea (COMISA)
Bibliographic record
Abstract
Obstructive sleep apnea (OSA) and insomnia are the two most prevalent sleep disorders, often co-occurring in a condition termed comorbid insomnia and sleep apnea (COMISA). While autonomic nervous system (ANS) dysfunction resulting from each of these disorders has been separately established through heart rate variability (HRV) analysis, the specific overnight ANS alterations due to COMISA have not been explored. This study aims to characterize nocturnal ANS alterations attributable to COMISA through time and frequency HRV analysis, distinguishing them from those of isolated insomnia or OSA. A total of 5,335 electrocardiograms from the Sleep Heart Health Study (SHHS) dataset were included in this research. Based on overnight polysomnography and sleep questionnaires, participants were categorized into No-OSA (2,738 subjects), Insomnia (190 subjects), OSA (2,260 subjects), or COMISA (147 subjects) groups. Classic time and frequency HRV features, along with specific frequency measures, were computed to characterize HRV behavior throughout the whole night, in both wakefulness and sleep periods. The analysis revealed that COMISA-specific ANS dysfunction manifests as reduced parasympathetic activity during wakefulness and heightened sympathetic activation during sleep. While primary ANS dysfunctions seem to result from recurrent apneic events affecting frequency features present in both OSA and COMISA, insomnia significantly alters mean heart rate during sleep, thus being the only feature distinguishing these two conditions. In conclusion, the combined effects of OSA and insomnia induce specific ANS dysfunction at night, highlighting the need for further HRV studies to better understand the impact of COMISA on ANS and its cardiovascular implications.Clinical trial registration: The clinical trial identifier of the original SHHS database is NCT00005275, https://sleepdata.org/datasets/shhs .
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".