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result(s) for
"Szabo, Charles Akos"
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Semiology of spontaneous generalized tonic‐clonic seizures in the epileptic baboon
by
González, David Andrés
,
Koneru, Sreekanth
,
Szabó, Charles Ákos
in
animals models
,
baboon
,
Biomarkers
2020
Objective The epileptic baboon provides an animal model for juvenile myoclonic epilepsy (JME), demonstrating spontaneous generalized tonic‐clonic seizures (GTCS) in addition to generalized myoclonic, absence and multifocal seizures. While photoconvulsive responses have been described in this model, spontaneous GTCS have not been characterized. Methods In this study, we characterized 46 seizures in 7 epileptic baboons (5 females, 12 ± 3 years old) by video recording. While housed in single cages, the baboons were monitored for a median of 2 (range 1‐10) weeks, with high‐resolution, infrared‐capable camera systems. Each GTCS was evaluated for evidence of preconvulsive ictal symptoms, focal convulsive behaviors, duration of the preconvulsive and convulsive periods, postictal immobility, and recovery of an upright posture. The circadian pattern of GTCS was also for each baboon. Results More than half of GTCS occurred in sleep, beginning from an upright position in all but one tethered baboon. Focal semiological findings were noted in 19 (41%) GTCS, and these included preconvulsive focal ictal motor behaviors as well as lateralized motor activity during the convulsions. The convulsive portion lasted 47 ± 10 seconds, whereas the entire seizure lasted 54 ± 21 seconds. Postictally, the baboons remained immobile for a median latency of 40 (range 14‐347) seconds, recovering an upright posture after 173 (range 71‐1980) seconds. GTCS demonstrated circadian patterns in all but one baboon, with 34 (74%) all seizures occurring between 1‐9 am. Significance GTCS in the baboon revealed intersubject variability, but semiology remained stereotyped in a given baboon. Similar to GTCS in people with JME, focal symptoms were also observed in epileptic baboons. The postictal recovery period, characterized by postictal immobility and myoclonus as well as time to recumbency, also varied among baboons.
Journal Article
Erratum
2020
[This corrects the article DOI: 10.1002/epi4.12388.].[This corrects the article DOI: 10.1002/epi4.12388.].
Journal Article
A companion to the development of common data elements for Sudden Unexpected Death in Epilepsy (SUDEP)
by
Faingold, Carl
,
Glasscock, Edward
,
O’Brien, Terence
in
additional phenotypes
,
Animals
,
Brain research
2025
Objective Sudden unexpected death in epilepsy (SUDEP) is a rare but devastating consequence of epilepsy and is the leading cause of death in people with epilepsy. SUDEP is associated with certain characteristics such as the presence of generalized tonic–clonic seizures, duration of epilepsy, and refractoriness to anti‐seizure medications. Despite insights from in vivo models, gaps persist in understanding the biological causes of SUDEP, leading to a lack of preventative tools. Current SUDEP preclinical models and data collection and reporting can vary widely across laboratories, hindering the direct translation of findings to humans. Methods The 2020 SUDEP Coalition Summit brought together a team of experts to chart areas of growth and tactics to address these areas. A critical research priority revealed during the summit was the development of data standardization tools to unify SUDEP research efforts. In response, CURE Epilepsy established a Steering Committee to oversee an effort to develop data standardization tools and worked with community members composed of experts in specific domains of SUDEP research to define these tools. Results Experts developed common data elements (CDEs) and case report forms (CRFs) to systematize preclinical SUDEP research. An accompanying publication describes the priority core and death‐related information CRF, while the current work describes supplemental CRFs that SUDEP researchers can use. Specifically, CDEs related to neurological variables, physiologic measures, therapeutics and pharmacology, neuroimaging, ex vivo electrophysiology, and additional phenotypes related to epilepsy are described. Significance Along with the core and death‐related CRF, supplemental CRFs can help the unification of SUDEP research by systematizing various endpoints. Adoption of these data standardization tools can also enhance collaboration between teams, hasten the translatability of SUDEP research to the human condition, and ultimately help prevent SUDEP. Plain Language Summary Preclinical sudden unexpected death in epilepsy (SUDEP) research holds great promise for addressing this fatal condition; however, lack of data standardization remains an issue. Other fields have shown that the incorporation of common data elements (CDEs) can serve to harmonize data across groups, increase rigor, and improve translatability. An accompanying paper describes “Core” CDEs that could be used by all SUDEP preclinical researchers; the current manuscript describes related, supplemental CDEs applicable to researchers depending on their specific scientific question. These include neurological and physiological measures, therapeutics and pharmacology, neuroimaging, ex vivo electrophysiology, and additional phenotypes related to epilepsy.
Journal Article
Enhancing sudden unexpected death in epilepsy (SUDEP) research through development of common data elements
by
Faingold, Carl
,
Glasscock, Edward
,
O’Brien, Terence
in
Animals
,
Biomedical Research - methods
,
case report form
2025
Objective Sudden Unexpected Death in Epilepsy (SUDEP) is a fatal complication for individuals living with epilepsy and is associated with significant personal and public burden. While certain neurotransmitters and neuronal pathways have been associated with SUDEP, the exact biological mechanisms are unknown. Preclinical research has been instrumental in providing clues to the underlying pathology but is limited by a lack of standardized methodologies for describing and collecting data. A key outcome of the Basic Science working group of the 2020 SUDEP Coalition Summit was the recognition that the development of standardized tools would greatly enhance SUDEP research. Such a research infrastructure would increase experimental rigor, repeatability, reproducibility, and transparency and finally, increase the chances that preclinical SUDEP research can be translated into human SUDEP. Methods CURE Epilepsy assembled a Steering Committee and working groups consisting of experts in preclinical and clinical SUDEP research to develop Common Data Elements (CDEs) and Case Report Forms (CRFs) to enable standardization and translation of preclinical SUDEP data. Standardized methodology from the development of other epilepsy‐related CDEs was used. Results The Core and Death‐Related Information CRF constitutes the priority CRF for SUDEP preclinical studies. This CRF gives investigators CDEs to note details of animal models used, experiment‐related information, and details about triggered and spontaneous seizures. The seizure‐related death information consists of CDEs related to observations at the time of death, characteristics of fatal seizures, the posture of the animal at the time of death, diet, medications, and any adverse health conditions. Significance Systematic use of CDEs and CRFs in SUDEP preclinical research can help increase the rigor and transparency of research. Core CDEs along with supplemental CDEs described in the accompanying manuscript can aid investigators and groups working together toward a common goal of preventing SUDEP. Plain Language Summary Sudden Unexpected Death in Epilepsy (SUDEP) is a fatal complication of epilepsy. Preclinical research holds promise in understanding and preventing SUDEP, but its impacts are limited due to a lack of data standardization and translation among research groups. Common data elements (CDEs) are essential pieces of information for a certain field of study. CURE Epilepsy brought together a team of researchers to develop CDEs that could serve as a blueprint for all SUDEP preclinical researchers. This paper describes the SUDEP Core and Death‐Related CDEs to be used with data elements presented in an accompanying paper.
Journal Article