Cardiorespiratory cross‐frequency coupling biomarker for sudden unexpected death in epilepsy
Bibliographic record
Abstract
OBJECTIVE: Sudden unexpected death in epilepsy (SUDEP) often follows generalized tonic-clonic seizures during sleep, likely resulting from impaired brainstem cardiorespiratory function. We used ictal electrocardiogram (ECG)-based cross-frequency phase-amplitude coupling (PAC) to detect cardiorespiratory disruptions, comparing SUDEP to non-SUDEP cohorts. Leveraging respiratory modulation of ECG signals can provide a robust indirect proxy of respiratory monitoring despite high-amplitude noise. METHODS: We analyzed ictal ECG and electroencephalographic recordings in 21 SUDEP cases and 21 non-SUDEP epilepsy controls. Ictal ECG segments from 76 seizures (38 SUDEP, 38 non-SUDEP) were processed using continuous wavelet transformation to compute PAC between respiratory (.1-.55 Hz, 6-33 breaths per minute) and cardiac (.7-3.7 Hz, 42-222 beats per minute) frequencies. Relative PAC coupling strength was evaluated for respiratory frequencies > .25 Hz (15 breaths per minute) and cardiac frequencies > 1.7 Hz (102 beats per minute). Furthermore, a 3 × 3 grid of PAC ranges was derived for each 20-s window, yielding 18 features (mean and SD) as inputs to a logistic regression model. RESULTS: Elevated ictal PAC at higher respiratory (>.25 Hz, p < .0001) and cardiac (>1.7 Hz, p < .0142) frequencies in SUDEP patients suggests ictal respiration modulates ictal tachycardia, leading to cardiorespiratory dysfunction, probably brainstem-mediated. The logistic model accurately distinguished 38 seizures in SUDEP cases from 38 seizures in non-SUDEP cases (receiver operating characteristic area under the curve = 91%). Seizures in SUDEP patients had higher propensity scores (p < .001) both per seizure and per patient. All six test seizures (three SUDEP, three non-SUDEP) were correctly classified using the optimal threshold. SIGNIFICANCE: Ictal ECG-based PAC analysis is a potential noninvasive biomarker for SUDEP risk, capturing cardiorespiratory dysregulation during seizures. Its integration into wearable ECG devices could enable real-time risk assessment, informing clinical interventions such as rescue medications, antiseizure medication adjustments, or surgical evaluations.
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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 | 0.001 | 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".