Neurogenic disturbances of cardiac rhythm

Arrhythmias are disturbances of electrical activation of the heart and are commonly encountered clinical conditions. Although typically associated with cardiac pathology, they have also been described in stroke and epilepsy. Two closely related structures, the insula and the temporal lobe, particularly the mesial region, have been implicated. Derangement of central autonomic control appears to be a key driver in neurogenic arrhythmogenesis and both these structures appear to play some role in influencing autonomic activity. Our understanding of this phenomenon is only in its infancy, and more research will be necessary to further it.peer-reviewe

Seizure detection using EEG and ECG signals for computer-based monitoring, analysis and management of epileptic patients

This is the accepted manuscript version of the following article: Iosif Mporas, “Seizure detection using EEG and ECG signals for computer-based monitoring, analysis and management of epileptic patients”, Expert Systems with Applications, Vol. 42(6), December 2014. The final published version is available at: http://www.sciencedirect.com/science/article/pii/S0957417414007763?via%3Dihub © 2014 Elsevier Ltd. All rights reserved.In this paper a seizure detector using EEG and ECG signals, as a module of a healthcare system, is presented. Specifically, the module is based on short-time analysis with time-domain and frequency-domain features and classification using support vector machines. The seizure detection module was evaluated on three subjects with diagnosed idiopathic generalized epilepsy manifested with absences. The achieved seizure detection accuracy was approximately 90% for all evaluated subjects. Feature ranking investigation and evaluation of the seizure detection module using subsets of features showed that the feature vector composed of approximately the 65%-best ranked parameters provides a good trade-off between computational demands and accuracy. This configurable architecture allows the seizure detection module to operate as part of a healthcare system in offline mode as well as in online mode, where real-time performance is needed.Peer reviewe

Is it possible to accurately differentiate neurocardiogenic syncope from epilepsy?

Global cerebral hypoperfusion resulting in syncope, and asynchronous discharge of cerebral neurons leading to seizure, are two major mechanisms of transient loss of consciousness. They both have a lot in common in clinical and historical settings, although with a high prevalence of incorrect diagnosis, even by well-trained staff. The aim of this review was to try to combine data from both a cardiologist’s and a neurologist’s perspective (history taking, special questionnaires, serum prolactin, EEG, CT/MRI, tilt-testing, loop recorders). (Cardiol J 2010; 17, 4: 420-427

The heart of epilepsy: Cardiac comorbidity and sudden death

The research described in this thesis aims to increase understanding of cardiac comorbidities and sudden unexpected death in epilepsy (SUDEP). People with epilepsy have a three-fold increased risk of dying prematurely compared to the general population. Common contributors to this are cardiovascular comorbidities, of which I provide an overview. Cardiovascular conditions and epilepsy can both lead to transient loss of consciousness (TLOC) with overlapping semiology. Particularly, myoclonic jerks which are commonly observed during syncope can be mistaken for signs of epilepsy. A misdiagnosis with detrimental consequences. I provide evidence that a careful analysis of motor phenomena can distinguish the two conditions. SUDEP is the commonest direct epilepsy-related premature death (UK >500 people/year). It typically occurs following convulsive seizures (CS). Most victims are found prone and some suggested people should sleep supine. I assessed video-EEG recordings of 180 CS and demonstrated peri-ictal positions often change, and most ending prone turned during CS. Sleeping supine is thus unlikely to prevent a postictal prone position and reduce risk of SUDEP. Pathomechanisms underlying SUDEP are likely a combination of interacting cardiorespiratory and autonomic factors. People with Dravet syndrome (DS) have a particular high SUDEP risk. I show that 49% of reported deaths in DS are SUDEP cases, most <10 years (78%). In DS, SCN1A mutations are mostly found, encoding a sodium channel expressed in brain and heart. DS mouse models suggest a key role for peri-ictal cardiac arrhythmias in SUDEP. I conducted a multicentre observational study and recorded 547 seizures in 45 DS participants. No major peri-ictal arrhythmias were found. Peri-ictal QTc-lengthening was, however, more common in DS than controls. This may reflect unstable repolarisation and increased propensity for arrhythmias. Prospective data to determine whether these peri-ictal variables can predict SUDEP risk is warranted

Ictal apnea: A prospective monocentric study in patients with epilepsy

Background and purpose: Ictal respiratory disturbances have increasingly been reported, in both generalized and focal seizures, especially involving the temporal lobe. Recognition of ictal breathing impairment has gained importance for the risk of sudden unexpected death in epilepsy (SUDEP). The aim of this study was to evaluate the incidence of ictal apnea (IA) and related hypoxemia during seizures. Methods: We collected and analyzed electroclinical data from consecutive patients undergoing long-term video-electroencephalographic (video-EEG) monitoring with cardiorespiratory polygraphy. Patients were recruited at the epilepsy monitoring unit of the Civil Hospital of Baggiovara, Modena Academic Hospital, from April 2020 to February 2022. Results: A total of 552 seizures were recorded in 63 patients. IA was observed in 57 of 552 (10.3%) seizures in 16 of 63 (25.4%) patients. Thirteen (81.2%) patients had focal seizures, and 11 of 16 patients showing IA had a diagnosis of temporal lobe epilepsy; two had a diagnosis of frontal lobe epilepsy and three of epileptic encephalopathy. Apnea agnosia was reported in all seizure types. Hypoxemia was observed in 25 of 57 (43.9%) seizures with IA, and the severity of hypoxemia was related to apnea duration. Apnea duration was significantly associated with epilepsy of unknown etiology (magnetic resonance imaging negative) and with older age at epilepsy onset (p&nbsp;&lt; 0.001). Conclusions: Ictal respiratory changes are a frequent clinical phenomenon, more likely to occur in focal epilepsies, although detected even in patients with epileptic encephalopathy. Our findings emphasize the need for respiratory polygraphy during long-term video-EEG monitoring for diagnostic and prognostic purposes, as well as in relation to the potential link of ictal apnea with the SUDEP risk

Migrating focal seizures and myoclonic status in ARV1-related encephalopathy

Objective: To report longitudinal clinical, EEG, and MRI findings in 2 sisters carrying compound heterozygous ARV1 mutations and exhibiting a peculiar form of developmental and epileptic encephalopathy (DEE). Neuropathologic features are also described in one of the sisters. Methods: Clinical course description, video-EEG polygraphic recordings, brain MRI, skin and muscle biopsies, whole-exome sequencing (WES), and brain neuropathology. Results: Since their first months of life, both girls exhibited severe axial hypotonia, visual inattention, dyskinetic movements, severe developmental delay, and slow background EEG activity. Intractable nonmotor seizures started in both at the eighth month of life, exhibiting the electroclinical characteristics of epilepsy of infancy with migrating focal seizures (EIMFS). In the second year of life, continuous epileptiform EEG activity of extremely high amplitude appeared in association with myoclonic status, leading to severely impaired alertness and responsiveness. Repeated brain MRI revealed progressive atrophic changes and severe hypomyelination. WES identified a compound heterozygous in the ARV1 gene [(p.Ser122Glnfs*7) and (p.Trp163*)] in one patient and was subsequently confirmed in the other. Both sisters died prematurely during respiratory infections. Postmortem neuropathologic examination of the brain, performed in one, revealed atrophic brain changes, mainly involving the cerebellum. Conclusions: This report confirms that biallelic ARV1 mutations cause a severe form of DEE and adds epilepsy with migrating focal seizures and myoclonic status to the spectrum of epilepsy phenotypes. Considering the potential role of human ARV1 in glycosylphosphatidylinositol (GPI) anchor biosynthesis, this severe syndrome can be assigned to the group of inherited GPI deficiency disorders, with which it shares remarkably similar clinical and neuroimaging features. ARV1 should be considered in the genetic screening of individuals with EIMFS

EEG signal classification using wavelet feature extraction and neural networks

Decision support systems have been utilised since 1960, providing physicians with fast and accurate means towards more accurate diagnoses and increased tolerance when handling missing or incomplete data. This paper describes the application of neural network models for classification of electroencephalogram (EEG) signals. Decision making was performed in two stages: initially, a feature extraction scheme using the wavelet transform (WT) has been applied and then a learning-based algorithm classifier performed the classification. The performance of the neural model was evaluated in terms of training performance and classification accuracies and the results confirmed that the proposed scheme has potential in classifying the EEG signals