Background: Ictal and postictal testing carried out in long-term epilepsy monitoring units is often sub-optimal. Recently, a European consensus protocol for testing patients during and after seizures was developed by a joint taskforce of the International League Against Epilepsy - Commission on European Affairs and the European Epilepsy Monitoring Unit Association.
Aim: Using this recently developed standardised assessment battery as a framework, the goal of this narrative review is to outline the proposed testing procedure in detail and explain the rationale for each individual component, focusing on the underlying neurobiology. This is intended to serve as an educational resource for staff working in epilepsy monitoring units.
Methods: A literature review of PubMed was performed; using the search terms "seizure", "ictal", "postictal", "testing", "examination", and "interview". Relevant literature was reviewed and relevant references were chosen. The work is presented as a narrative review.
Results: The proposed standardised assessment battery provides a comprehensive and user-friendly format for ictal-postictal testing, and examines consciousness, language, motor, sensory, and visual function.
Conclusion: The standardised approach proposed has the potential to make full use of data recorded during video EEG increasing the diagnostic yield with regards to lateralisation and localisation, aiding both presurgical and diagnostic studies.
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http://dx.doi.org/10.1016/j.seizure.2019.08.008 | DOI Listing |
J Clin Neurophysiol
January 2025
Department of Neurology, Washington University in St Louis, St. Louis, MO.
Purpose: Continuous EEG (cEEG) monitoring is increasingly used in the management of neonates with seizures. There remains debate on what clinically relevant information can be gained from cEEG in neonates with suspected seizures, at high risk for seizures, or with definite seizures, as well as the use of cEEG for prognosis in a variety of conditions. In this guideline, we address these questions using American Clinical Neurophysiology Society structured methodology for clinical guideline development.
View Article and Find Full Text PDFACS Nano
January 2025
School of Mechanical and Manufacturing Engineering, University of New South Wales, Sydney, New South Wales 2052, Australia.
Implantable systems with chronic stability, high sensing performance, and extensive spatial-temporal resolution are a growing focus for monitoring and treating several diseases such as epilepsy, Parkinson's disease, chronic pain, and cardiac arrhythmias. These systems demand exceptional bendability, scalable size, durable electrode materials, and well-encapsulated metal interconnects. However, existing chronic implantable bioelectronic systems largely rely on materials prone to corrosion in biofluids, such as silicon nanomembranes or metals.
View Article and Find Full Text PDFCNS Drugs
January 2025
Cornwall Intellectual Disability Equitable Research (CIDER), University of Plymouth, Truro, England.
There is a synergistic relationship between epilepsy and intellectual disability (ID), and the approach to managing people with these conditions needs to be holistic. Epilepsy is the main co-morbidity associated with ID, and clinical presentation tends to be complex, associated with higher rates of treatment resistance, multi-morbidity and premature mortality. Despite this relationship, there is limited level 1 evidence to inform treatment choice for this vulnerable population.
View Article and Find Full Text PDFFront Neurol
December 2024
Division of Neurology, Department of Pediatrics, McMaster Children's Hospital, Hamilton, ON, Canada.
Introduction: This study investigated low-density scalp electrical source imaging of the ictal onset zone and interictal spike ripple high-frequency oscillation networks using source coherence maps in the pediatric epilepsy surgical workup. Intracranial monitoring, the gold standard for determining epileptogenic zones, has limited spatial sampling. Source coherence analysis presents a promising new non-invasive technique.
View Article and Find Full Text PDFFront Pharmacol
December 2024
Department of Pharmacy, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
Aims: Few personalized monitoring models for valproic acid (VPA) in pediatric epilepsy patients (PEPs) incorporate machine learning (ML) algorithms. This study aimed to develop an ensemble ML model for VPA monitoring to enhance clinical precision of VPA usage.
Methods: A dataset comprising 366 VPA trough concentrations from 252 PEPs, along with 19 covariates and the target variable (VPA trough concentration), was refined by Spearman correlation and multicollinearity testing (366 × 11).
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