Cardiorespiratory cross‐frequency coupling biomarker for sudden unexpected death in epilepsy

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.