RESUMEN
Background: Ictal bradycardia (IB) and asystole (IA) represent a rare but potentially harmful feature of epileptic seizures. The aim of this study was to study IB/IA in patients with sleep-related hypermotor epilepsy (SHE). Methods: We retrospectively included cases with video-EEG-confirmed SHE who attended our Institute up to January 2021. We reviewed the ictal polysomnography recordings focusing on ECG and identified cases with IB (R-R interval ≥ 2 s or a ≥10% decrease of baseline heart rate) and IA (R-R interval ≥ 4 s). Results: We included 200 patients (123 males, 61.5%), with a mean age of 42 ± 16 years. Twenty patients (20%) had focal cortical dysplasia (FCD) on brain MRI. Eighteen (out of 104 tested, 17.3%) carried pathogenic variants (mTOR pathway, n = 10, nAchR subunits, n = 4, KCNT1, n = 4). We identified IB/IA in four cases (2%): three had IA (mean 10 s) and one had IB. Three patients had FCD (left fronto-insular region, left amygdala, right mid-temporal gyrus) and two had pathogenic variants in DEPDC5; both features were more prevalent in patients with IB/IA than those without (p = 0.003 and p = 0.037, respectively). Conclusions: We identified IB/IA in 2% of patients with SHE and showed that this subgroup more frequently had FCD on brain MRI and pathogenic variants in genes related to the mTOR pathway.
RESUMEN
The most critical burden for People with Epilepsy (PwE) is represented by seizures, the unpredictability of which severely impacts quality of life. The design of real-time warning systems that can detect or even predict ictal events would enhance seizure management, leading to high benefits for PwE and their caregivers. In the past, various research works highlighted that seizure onset is anticipated by significant changes in autonomic cardiac control, which can be assessed through heart rate variability (HRV). This manuscript conducted a scoping review of the literature analyzing HRV-based methods for detecting or predicting ictal events. An initial search on the PubMed database returned 402 papers, 72 of which met the inclusion criteria and were included in the review. These results suggest that seizure detection is more accurate in neonatal and pediatric patients due to more significant autonomic modifications during the ictal transitions. In addition, conventional metrics are often incapable of capturing cardiac autonomic variations and should be replaced with more advanced methodologies, considering non-linear HRV features and machine learning tools for processing them. Finally, studies investigating wearable systems for heart monitoring denoted how HRV constitutes an efficient biomarker for seizure detection in patients presenting significant alterations in autonomic cardiac control during ictal events.
RESUMEN
Sudden unexpected death in epilepsy (SUDEP) is a sudden, unexpected, witnessed or unwitnessed, non-traumatic and non-drowning death, occurring in benign circumstances, in an individual with epilepsy, with or without evidence for a seizure and excluding documented status epilepticus in which postmortem examination does not reveal other causes of death. Lower diagnostic levels are assigned when cases met most or all of these criteria, but data suggested more than one possible cause of death. The incidence of SUDEP ranged from 0.09 to 2.4 per 1000 person-years. Differences can be attributed to the age of the study populations (with peaks in the 20-40-year age group) and the severity of the disease. Young age, disease severity (in particular, a history of generalized TCS), having symptomatic epilepsy, and the response to antiseizure medications (ASMs) are possible independent predictors of SUDEP. The pathophysiological mechanisms are not fully known due to the limited data available and because SUDEP is not always witnessed and has been electrophysiologically monitored only in a few cases with simultaneous assessment of respiratory, cardiac, and brain activity. The pathophysiological basis of SUDEP may vary according to different circumstances that make that particular seizure, in that specific moment and in that patient, a fatal event. The main hypothesized mechanisms, which could contribute to a cascade of events, are cardiac dysfunction (included potential effects of ASMs, genetically determined channelopathies, acquired heart diseases), respiratory dysfunction (included postictal arousal deficit for the respiratory mechanism, acquired respiratory diseases), neuromodulator dysfunction, postictal EEG depression and genetic factors.