Incidence and Types of Cardiac Arrhythmias in the Peri-Ictal Period in Patients Having a Generalized Convulsive Seizure

Abstract

Background and objectives: Generalized convulsive seizures (GCSs) are the main risk factor of sudden unexpected death in epilepsy (SUDEP), which is likely due to peri-ictal cardiorespiratory dysfunction. The incidence of GCS-induced cardiac arrhythmias, their relationship to seizure severity markers, and their role in SUDEP physiopathology are unknown. The aim of this study was to analyze the incidence of seizure-induced cardiac arrhythmias, their association with electroclinical features and seizure severity biomarkers, as well as their specific occurrences in SUDEP cases.

Methods: This is an observational, prospective, multicenter study of patients with epilepsy aged 18 years and older with recorded GCS during inpatient video-EEG monitoring for epilepsy evaluation. Exclusion criteria were status epilepticus and an obscured video recording. We analyzed semiologic and cardiorespiratory features through video-EEG (VEEG), electrocardiogram, thoracoabdominal bands, and pulse oximetry. We investigated the presence of bradycardia, asystole, supraventricular tachyarrhythmias (SVTs), premature atrial beats, premature ventricular beats, nonsustained ventricular tachycardia (NSVT), atrial fibrillation (Afib), ventricular fibrillation (VF), atrioventricular block (AVB), exaggerated sinus arrhythmia (ESA), and exaggerated sinus arrhythmia with bradycardia (ESAWB). A board-certified cardiac electrophysiologist diagnosed and classified the arrhythmia types. Bradycardia, asystole, SVT, NSVT, Afib, VF, AVB, and ESAWB were classified as arrhythmias of interest because these were of SUDEP pathophysiology value. The main outcome was the occurrence of seizure-induced arrhythmias of interest during inpatient VEEG monitoring. Moreover, yearly follow-up was conducted to identify SUDEP cases. Binary logistic generalized estimating equations were used to determine clinical-demographic and peri-ictal variables that were predictive of the presence of seizure-induced arrhythmias of interest. The z-score test for 2 population proportions was used to test whether the proportion of seizures and patients with postconvulsive ESAWB or bradycardia differed between SUDEP cases and survivors.

Results: This study includes data from 249 patients (mean age 37.2 ± 23.5 years, 55% female) who had 455 seizures. The most common arrhythmia was ESA, with an incidence of 137 of 382 seizures (35.9%) (106/224 patients [47.3%]). There were 50 of 352 seizure-induced arrhythmias of interest (14.2%) in 41 of 204 patients (20.1%). ESAWB was the commonest in 22 of 394 seizures (5.6%) (18/225 patients [8%]), followed by SVT in 18 of 397 seizures (4.5%) (17/228 patients [7.5%]). During follow-up (48.36 ± 31.34 months), 8 SUDEPs occurred. Seizure-induced bradycardia (3.8% vs 12.5%, z = -16.66, p < 0.01) and ESAWB (6.6% vs 25%; z = -3.03, p < 0.01) were over-represented in patients who later died of SUDEP. There was no association between arrhythmias of interest and seizure severity biomarkers (p > 0.05).

Discussion: Markers of seizure severity are not related to seizure-induced arrhythmias of interest, suggesting that other factors such as occult cardiac abnormalities may be relevant for their occurrence. Seizure-induced ESAWB and bradycardia were more frequent in SUDEP cases, although this observation was based on a very limited number of SUDEP patients. Further case-control studies are needed to evaluate the yield of arrhythmias of interest along with respiratory changes as potential SUDEP biomarkers.