Classification Of Epilepsy Syndromes Research Articles

Pediatric epilepsy syndromes with associated developmental impairment.

In 2022, the International League Against Epilepsy revised their classification of epilepsy syndromes for clinicians to better understand the relationships between different epilepsy syndromes, their underlying causes, and their associated developmental and behavioral features. This review highlights portions of the current classification with an emphasis on epilepsy syndromes that readily present with developmental challenges and provides a unique framework, based on electroencephalography, to easily identify and understand these syndromes. Included in this review are a helpful categorization scheme with visual aid, descriptions of updated epilepsy syndromes, figures of relevant identifiers of syndrome and information regarding future directions toward treatment and research. Covered syndromes include developmental and epileptic encephalopathy, Dravet syndrome, Rasmussen syndrome, and infantile epileptic spasm syndrome, among others. WHAT THIS PAPER ADDS: The revised epilepsy syndrome classification by the International League Against Epilepsy aims to improve the outcomes for children with epilepsy. The electroencephalography features of epilepsy syndromes are grouped based on a categorization model. This model allows clinicians to understand overlapping phenotypes and aid with both identification and diagnosis.

New International League Against Epilepsy Epilepsy Syndrome Classification: Classification and Definition of Epilepsy Syndromes with Onset at a Variable Age

New International League Against Epilepsy Epilepsy Syndrome Classification: Classification and Definition of Epilepsy Syndromes with Onset at a Variable Age

Disorders related to antineuronal antibodies: Autoimmune epilepsy

AbstractAutoimmune epilepsy is characterized as a subtype of autoimmune encephalitis, where epileptic seizures serve as the primary or predominant manifestation of the disease. Among patients who are refractory to antiepileptic drug therapy, a part of them experience improved seizure control with immunotherapy. Some of these individuals have been found to possess autoantibodies that target the neuronal surface, intracellular, or extracellular antigens. In 2017, the International League Against Epilepsy (ILAE) proposed a new classification of epilepsy syndromes that, for the first time, recognized “immune” as one of the etiologies of epilepsy. Since early and prompt diagnosis and treatment of autoimmune epilepsy may improve the prognosis, it is crucial to actively consider the utilization of reported diagnostic features and treatment with immunotherapy in the management of patients with refractory epilepsy. We herein provide a review of the literature concerning the clinical features, laboratory findings, pathophysiology, and treatment options associated with this disease.

The Contribution of Argentine Neurologists to the Description of Infantile Epileptic Spasms Syndrome and Related Epileptic and Nonepileptic Neurological Conditions

AbstractIn the latest report of the International League against Epilepsy Task Force on Nosology and Definitions on the methodology for classification of epilepsy syndromes, the term infantile epileptic spasms syndrome (IESS) was chosen for what were previously called infantile spasms, including West syndrome and infantile epileptic spasms without hypsarrhythmia.Different Argentine groups have contributed to the description of IESS and related epileptic and nonepileptic syndromes. Here we aimed to review studies by different Argentine authors that contributed to the development of the definitions of IESS and its most important benign differential diagnosis.In 1949, Vazquez and Turner from Argentina first recognized a clinical-electroencephalographic correlate of the entity described by Dr. West defining the triad of epileptic spasms, diffuse paroxysmal cerebral dysrhythmia, and psychomotor impairment. Subsequently, in 1976 Fejerman first reported 10 neurologically normal infants with recurrent spells that resembled epileptic spasms. As neurological status, electroencephalogram (EEG), and outcomes were normal, these infants were clearly different from those with West syndrome or epileptic spasms without hypsarrhythmia.Since 2003, Caraballo et al have published different series of patients with epileptic spasms in clusters without hypsarrhythmia occurring in infancy. Before the onset of the epileptic spasms in clusters, these infants were often normal and they had focal or generalized EEG abnormalities.Publication in local journals in languages other than English may lead to the loss of important data found by colleagues from different geographic areas. Therefore, this should be followed by publication in English in peer-reviewed journals.

Regional Scalp EEGs Analysis and Classification on Typical Childhood Epilepsy Syndromes

Epilepsy syndromes are typical childhood nervous system diseases, that may include different types of epilepsy seizures commonly seen, but far more complex than seizures. Accurate classification of epilepsy syndromes is crucial for diagnosis and treatment. Scalp electroencephalogram (EEG) provides a favorable basis for clinical diagnosis of epilepsy syndrome. In this paper, we present a comprehensive analysis on the correlation between time/frequency-domain regional scalp EEG features and typical epilepsy syndromes, and proposes a transfer network-based classification model for epilepsy syndromes. Results on 63 children suffered from 4 typical epilepsy syndromes and 19 children from the normal control groups (NCGs) show that: 1) The features of the frontal polar region and the frontal region are always very similar, and the parietal region and the occipital region have similar features for each syndrome; 2) Skewness is the most significant feature and Lemp-Ziv complexity (LZC) has the least contribution to distinguishing childhood epilepsy syndromes/NCGs; 3) Different individuals of the same syndrome have similarities, while the EEG characteristics of different syndromes are significantly different. A ResNet50 model based on deep transfer feature learning is applied to perform epilepsy syndromes/NCGs classification. The results show that feature selection based on the feature significance testing and correlation analysis can well enhance the classification performance.

Epilepsy with myoclonic absences: A case series

Epilepsy with myoclonic absences (EMA) is a very rare childhood generalized epilepsy syndrome (<1% of all generalized epilepsies) associated with frequent myoclonic absence seizures that was described in 1969 by Tassinari et al. [ [1] Tassinari C.A. Lyagoubi S. Santos V. et al. Study on spike and wave discharges in man. II. Clinical and electroencephalographic aspects of myoclonic absences. Rev Neurol. 1969; 121: 379-383 PubMed Google Scholar ]. Seizures are characterized by bilateral rhythmic jerks of the upper limbs, superimposed on tonic abduction of the arms [ [2] Bureau M. Tassinari C.A. Epilepsy with myoclonic absences. Brain Dev. 2005; 27: 178-184 Abstract Full Text Full Text PDF PubMed Scopus (46) Google Scholar ]. Ictal EEG consists of 3-Hz generalized spike-and-wave complexes that are time-locked with the upper limb myoclonus, while the EMG generally shows myoclonic jerks followed by tonic contraction of both deltoids. These seizures differ from typical absences of childhood absence epilepsy, since myoclonic jerks are generally not seen in typical absences and, if present, are subtle and spare the arms. The lack of an atonic component also distinguishes these seizures from myoclonic-atonic seizures [ [3] Specchio N. Wirrell E.C. Scheffer I.E. et al. International league against epilepsy classification and definition of epilepsy syndromes with onset in childhood: position paper by the ILAE Task Force on Nosology and Definitions. Epilepsia. 2022; 63: 1398-1442 Crossref PubMed Scopus (46) Google Scholar ]. A recent position paper by the International League Against Epilepsy for the classification of epilepsy syndromes with onset in childhood retained EMA as an independent epilepsy syndrome and defined its diagnostic criteria [ [3] Specchio N. Wirrell E.C. Scheffer I.E. et al. International league against epilepsy classification and definition of epilepsy syndromes with onset in childhood: position paper by the ILAE Task Force on Nosology and Definitions. Epilepsia. 2022; 63: 1398-1442 Crossref PubMed Scopus (46) Google Scholar ]. The mandatory requirements are myoclonic absences as the predominant type of seizures, and regular 3 Hz generalized spike-and-wave complexes synchronous with myoclonus.

Two-Stream Attention 3-D Deep Network-Based Childhood Epilepsy Syndrome Classification

Epilepsy syndromes are typical childhood nervous system diseases, usually containing several different seizure types commonly seen. There exist around 20 known childhood epilepsy syndromes and accurate classifying these epilepsy syndromes plays a vital guidance to diagnosis and treatment. Current research mainly focused on seizure detection, while few have been presented on epilepsy syndrome classification. In this article, a novel two-stream 3-D attention module-based deep network (TSA3-D) is developed to exploit multichannel time-frequency and frequency-space features of interictal EEGs for epilepsy syndrome classification. Two multichannel montage transforms are applied for EEG feature optimization to reduce artifact affection. In TSA3-D, both the channelwise attention (CA) and dual spatial attention (DSA)-based 3-D attention modules are developed to enhance the EEG feature learning capability. The study is conducted on the long-term interictal EEGs of 115 subjects from the Children’s Hospital, Zhejiang University School of Medicine (CHZU). These data belong to seven typical childhood epilepsy syndromes and one normal control group. Experimental results show that TSA3-D can achieve an overall accuracy of 99.52%, the highest among when compared with the state-of-the-art (SOTA) methods.

DSMN-ESS: Dual-Stream Multitask Network for Epilepsy Syndrome Classification and Seizure Detection

DSMN-ESS: Dual-Stream Multitask Network for Epilepsy Syndrome Classification and Seizure Detection

3D figure of epilepsy syndromes.

We propose an instructive figure that summarized the classification of epilepsy syndromes according to the 2022 report of the ILAE Task Force on Nosology and Definitions. Our aim is to present on the same figure different concepts such as the names of epilepsy syndromes, their extreme and classical ages of onset, their epilepsy types (generalized, focal, or generalized and focal) but also their membership in groups of epilepsy syndromes as for self-limited or developmental and epileptic encephalopathies. With this figure, we provide an interactive tool, as supplementary data, helping to present this classification and link it to electro-clinical mandatory, alerts, and exclusionary criteria of each syndrome, in accordance with the ILAE position papers on syndromes classification and nosology. This report may be used as an illustrative tool for teaching epilepsy syndromes and as a practical and comprehensive aid for the classification of epilepsy individuals' syndromes.

Classification and definition of epilepsy. Position paper by the International League Against Epilepsy on Nosology and Definitions of Epilepsy Syndromes dated 2021

This article presents updated and revised diagnostic criteria for epilepsy syndromes proposed in 2021 by the Nosology and Definitions Taskforce of the International League Against Epilepsy (ILAE). The current classification of epilepsy syndromes was developed in 1989. The new ILAE Classification and Definition of Epilepsy Syndromes is a result of huge work of many experts from all over the world. The draft of the new classification is presented on the ILAE website for wide discussion. It includes 4 main sections: 1) classification and definition of epilepsy syndrome with onset in neonates and infants; 2) classification and definition of epilepsy syndromes with onset in childhood; 3) classification and definition of epilepsy syndromes with onset at a variable age; 4) definition of the idiopathic generalized epilepsy syndromes. Each section is based on a thorough analysis of literature and clinical experience of experts. Its main purpose is to identify epilepsy syndromes using the 2017 ILAE classification of epilepsy forms and types of epileptic seizures, as well as to identify specific characteristics of each syndrome to improve clinical diagnosis. For each syndrome, the document provides the details on its epidemiology, clinical manifestations, types of seizures, electroencephalographic features, neuroimaging signs, genetic examination, as well as differential diagnosis with other epilepsy syndromes and various non-epileptic conditions. It introduces mandatory criteria that must be present in order to diagnose the syndrome and alert criteria that are absent in the vast majority of cases within a syndrome, but rarely can be seen. Particular attention is paid to exclusionary criteria that must be absent in order to diagnose the syndrome. When developing the criteria for each epilepsy syndrome, the ILAE Task Force used the latest literature data, including Internet resources and the opinion of experts in this area. The international classification should be applied by specialists from all over the world. It should contain clear and easy-to-understand definitions; the language should be simple and understandable. The new ILAE classification demonstrates revised definitions of well-known electroclinical epilepsy syndromes and proposes a new concept of defining epilepsy syndromes by their etiology (including those syndromes in which pathogenic mutations or structural changes correlate significantly with certain electroclinical phenotype). It also introduces a new etiology-defined class of epilepsy syndromes characterized by specific genetic, metabolic, and structural causes. The document does not cover therapy for epilepsy syndromes; however, for some of them, it specifies the most effective or potentially aggravating antiepileptic drugs. The prospect of further targeted gene therapies development and approval of antiepileptic drugs specific for certain epilepsy syndromes after randomized clinical trials had served as a powerful motivation to introduce the concept of epilepsy syndromes determined primarily by etiology. In conclusion, the authors discuss the Classification and Definition of Epilepsy Syndromes, propose their ideas, comments, suggestions, and observations. This article aims to familiarize a wide range of specialists with the new ILAE classification and its details. In addition to a detailed description of the abovementioned document, the article provides information on the currently existing classification principles for epilepsy and epileptic seizures. There is also a discussion with the authors’ comments on the ILAE Classification and Definition of Epilepsy Syndromes.

Methodology for classification and definition of epilepsy syndromes with list of syndromes: Report of the ILAE Task Force on Nosology and Definitions.

Epilepsy syndromes have been recognized for >50years, as distinct electroclinical phenotypes with therapeutic and prognostic implications. Nonetheless, no formally accepted International League Against Epilepsy (ILAE) classification of epilepsy syndromes has existed. The ILAE Task Force on Nosology and Definitions was established to reach consensus regarding which entities fulfilled criteria for an epilepsy syndrome and to provide definitions for each syndrome. We defined an epilepsy syndrome as "a characteristic cluster of clinical and electroencephalographic features, often supported by specific etiological findings (structural, genetic, metabolic, immune, and infectious)." The diagnosis of a syndrome in an individual with epilepsy frequently carries prognostic and treatment implications. Syndromes often have age-dependent presentations and a range of specific comorbidities. This paper describes the guiding principles and process for syndrome identification in both children and adults, and the template of clinical data included for each syndrome. We divided syndromes into typical age at onset, and further characterized them based on seizure and epilepsy types and association with developmental and/or epileptic encephalopathy or progressive neurological deterioration. Definitions for each specific syndrome are contained within the corresponding position papers.

Introduction to the epilepsy syndrome papers.

The epilepsies comprise a broad group of disorders/diseases with diverse etiologies, diverse electroclinical presentations, and marked variability in clinical outcomes. The 2017 International League Against Epilepsy (ILAE) Classification of the Epilepsies defined three diagnostic levels including (1) seizure type, (2) epilepsy type, and (3) epilepsy syndrome, emphasizing that etiology and comorbidities must be considered at each level.1 Although epilepsy syndromes had been recognized as distinct electroclinical entities long before the first ILAE Classification of Epilepsies and Epilepsy Syndromes was proposed in 1985, and have been summarized in the Guide Bleu and Epileptic Syndromes in Infancy, Childhood, and Adolescence,2 there was no formally accepted ILAE classification of epilepsy syndromes. This series of ILAE position papers represents the work of the Nosology and Definitions Task Force, established by the ILAE in 2017 to provide definitions of epilepsy syndromes. We defined an epilepsy syndrome as “a characteristic cluster of clinical and EEG features, often supported by specific etiological findings (structural, genetic, metabolic, immune, and infectious).” The diagnosis of a syndrome in an individual with epilepsy frequently carries prognostic and treatment implications. Syndromes often have age-dependent presentations, meaning that they typically start at specific ages, and in some cases may also remit at certain ages. Many syndromes are strongly correlated with a range of specific intellectual, psychiatric, and other comorbidities, whereas in other syndromes, the absence of such comorbidities is a characteristic feature (Figure 1). Epilepsy syndromes have traditionally been grouped according to age at onset. Accordingly, the ILAE position papers describe separately syndromes with onset in neonates and infants (up to age 2 years), syndromes with onset in childhood, and syndromes that may begin at variable ages (meaning in both pediatric and adult patients). Additionally, a separate position paper on the idiopathic generalized epilepsies is included. The syndromes are further subdivided into generalized, focal, or generalized and focal, based on seizure type(s), with a separate category for syndromes with developmental and epileptic encephalopathy (DEE) or progressive neurological deterioration. The 2017 Classification of the Epilepsies proposed the term DEE to denote an epilepsy associated with developmental impairment that may be due to both the underlying etiology (developmental encephalopathy) and superimposed epileptic activity (epileptic encephalopathy).1 Most DEEs present very early in life; the term DEE is more challenging to apply when epilepsy begins later, following a prolonged period of normal development. Thus, the ILAE Nosology and Definitions Task Force identified syndromes with DEE and syndromes with progressive neurological deterioration. This approach clearly identifies the group of syndromes associated with cognitive impairment with or without other manifestations of neurological deterioration and recognizes that this impairment may be due to the underlying etiology, superimposed epileptic activity, or both. Furthermore, the ILAE Nosology and Definitions Task Force identified the concept of etiology-specific syndrome, to denote clearly defined entities with a distinct phenotype associated with a specific etiology, examples of which include certain monogenic epilepsies, such as CDKL5-DEE and PCDH19 clustering epilepsy, and structural entities such as mesial temporal lobe epilepsy with hippocampal sclerosis and gelastic seizures with hypothalamic hamartoma. In the current classification, a number of epilepsies with specific etiologies as well as some epilepsies that arise from or involve specific brain regions or networks have not been included as syndromes, although these often also have a characteristic cluster of clinical and electroencephalographic (EEG) features. Further work is needed to extend the range of epilepsies included in the ILAE syndrome classification and to determine whether some of those conditions meet criteria for classification as epilepsy syndromes. None. E.W. has served as a paid consultant for Encoded Therapeutics and Biomarin. She is the Editor-in-Chief of Epilepsy.com. P.T. has received speaker's or consultancy fees from Arvelle, Eisai, GW Pharma, LivaNova, UCB Pharma, Xenon Pharma, and Zogenix. E.P. has received speaker and/or consultancy fees from Angelini, Arvelle, Biogen, Biopas, Eisai, GW Pharma, Sanofi group of companies, SK Life Science, Takeda, UCB Pharma, Xenon Pharma, and Zogenix and royalties from Wiley, Elsevier, and Wolters Kluwer. S.L.M. is the Charles Frost Chair in Neurosurgery and Neurology and acknowledges grant support from the NIH (U54 NS100064, NS43209), the US Department of Defense (W81XWH-18–1–0612), the Heffer Family and Segal Family Foundations, and the Abbe Goldstein/Joshua Lurie and Laurie Marsh/Dan Levitz families. S.L.M. is serving as Associate Editor of Neurobiology of Disease. He is on the editorial board of Brain and Development, Pediatric Neurology, Annals of Neurology, MedLink, and Physiological Research. He receives compensation from Elsevier for his work as Associate Editor of Neurobiology of Disease and from MedLink for his work as Associate Editor and royalties from two books he coedited. We confirm that we have read the Journal's position on issues involved in ethical publication and affirm that this report is consistent with those guidelines.

3D residual-attention-deep-network-based childhood epilepsy syndrome classification

Interictal electroencephalograms (EEGs) usually contain important information for epilepsy analysis and diagnosis. However, the focus of existing research has mainly been on epilepsy seizure onset detection, and only a few studies have been conducted on childhood epilepsy syndrome classification, which is usually more complicated than seizure detection. In this study, a novel 3D residual-attention-module-based deep network (AR3D) is developed to explore the spatial and time–frequency features of multichannel EEGs. The interictal EEGs of 37 patients with five typical childhood epilepsy syndromes, namely, benign childhood epilepsy with centrotemporal spikes, childhood absence epilepsy, febrile seizures plus, infantile spasms, unknown epilepsy syndrome, and one control group, are studied. The proposed AR3D algorithm, with a 97.03% F1 score, outperforms several state-of-the-art 2D and 3D convolution deep networks.

Deep feature fusion based childhood epilepsy syndrome classification from electroencephalogram

Accurate classification of the children’s epilepsy syndrome is vital to the diagnosis and treatment of epilepsy. But existing literature mainly focuses on seizure detection and few attention has been paid to the children’s epilepsy syndrome classification. In this paper, we present a study on the classification of two most common epilepsy syndromes: the benign childhood epilepsy with centro-temporal spikes (BECT) and the infantile spasms (also known as the WEST syndrome), recorded from the Children’s Hospital, Zhejiang University School of Medicine (CHZU). A novel feature fusion model based on the deep transfer learning and the conventional time–frequency representation of the scalp electroencephalogram (EEG) is developed for the epilepsy syndrome characterization. A fully connected network is constructed for the feature learning and syndrome classification. Experiments on the CHZU database show that the proposed algorithm can offer an average of 92.35% classification accuracy on the BECT and WEST syndromes and their corresponding normal cases.

Genetic diagnosis and clinical characteristics by etiological classification in early-onset epileptic encephalopathy with burst suppression pattern

BackgroundEarly-onset epileptic encephalopathies with burst suppression (EOEE-BS) are a group of neonatal epileptic syndromes characterized by intractable epilepsy and severe psychomotor delay with structural and metabolic factors accounting for major etiologies. However, recent advances in gene sequencing have identified that genetic factors might also play a significant role in the development of EOEE-BS. Herein, we used various genetic tests to identify pathogenic genetic variants in EOEE-BS irrespective of structural malformations and analyzed the clinical features associated with each different etiology. MethodsA total of 48 patients with EOEE-BS were included. Except for patients with severe hypoxic damage, patients with structural malformations were included in our patient cohort. Clinical features of the patients were reviewed, and etiological diagnoses were made based on several genetic tests, metabolic studies, and radiological findings. ResultA genetic diagnosis was made in 31 (64.6 %) patients, with the most commonly diagnosed gene being STXBP1 (n = 13, 27.1 %), followed by KCNQ2 (n = 5, 10.4 %), SCN2A (n = 5, 10.4 %), DEPDC5 (n = 3, 6.3 %), CASK (n = 1, 2.1 %), CDKL5 (n = 1, 2.1 %), GNAO1 (n = 1, 2.1 %), SLC6A8 (n = 1, 2.1 %), and LIS1 deletion (n = 1, 2.1 %). Other than the classification of epilepsy syndrome, no clinical features were associated with the genetically diagnosed group. Among eight patients with structural malformations, genetic diagnosis was achieved in five (62.5 %), and those patients had pathogenic mutations in DEPDC5 and CASK or LIS1 deletion, indicating the significance of gene sequencing irrespective of structural abnormalities. Treatment responses to a variety of medications and the ketogenic diet differed by etiology, and surgical resection proved to be effective in patients with cortical dysplasia. ConclusionGenetic etiologies are an important factor in EOEE-BS irrespective of structural malformations and the treatment options may differ by etiology.

The Role of EEG in the Diagnosis and Classification of Epilepsy Syndromes: A Tool for Clinical Practice by the ILAE Neurophysiology Task Force

The Role of EEG in the Diagnosis and Classification of Epilepsy Syndromes: A Tool for Clinical Practice by the ILAE Neurophysiology Task Force

Epilepsia

Epilepsy is a very prevalent condition, requiring a correct identification. Epilepsy patient remains stigmatized socially. In 2017, ILAE has proposed a new classification of epilepsy syndromes and its seizures, provided a universal vocabulary, more practical, operational and flexible. Ambiguous terms (like complex partial, secondarily generalized, psychic and dyscognitive epilepsy) have disappeared. Etiologies are grouped in six categories (genetic, structural, metabolic, immune, infectious and unknown). Anamnesis and electroencephalogram continue to be the essential pillars for the diagnostic of epileptic seizures.

Evolution and course of early life developmental encephalopathic epilepsies: Focus on Lennox-Gastaut syndrome.

Developmental encephalopathic epilepsies (DEEs) are characterized by refractory seizures, disability, and early death. Opportunities to improve care and outcomes focus on West syndrome/infantile spasms (WS/IS). Lennox-Gastaut syndrome (LGS) is almost as common but receives little attention. We examined initial presentations of DEEs and their evolution over time to identify risk and indicators of developing LGS. Data are from the Connecticut Study of Epilepsy, a prospective, longitudinal study of 613 children with newly diagnosed epilepsy recruited in 1993-1997. Central review of medical records permitted classification of epilepsy syndromes at diagnosis and at reclassification 2, 5, and 9years later. DEEs were compared to other epilepsies for seizure and cognitive outcomes and mortality. Analyses examined the evolution of DEE syndromes after initial presentation, with specific comparisons made between WS/IS and LGS. Statistical analyses were performed with t tests and chi-square tests. Fifty-eight children (9.4%) had DEEs, median onset age=1.1years (interquartile range ([IQR]0.3-1.3) in DEEs and 6.0years (IQR3.0-9.0) in other epilepsies (P<0.001). DEEs vs other epilepsies had more pharmacoresistance (71% vs 18%), intellectual disability (84% vs 11%), and mortality (21% vs <1%; all P<0.001). During follow-up, the form of epilepsy evolved in 33 children. WS/IS was the most common initial diagnosis (N=23) and in 5 children WS/IS evolved later. LGS was diagnosed initially in 4 children (1 later revised) and in 22 by the end of follow-up, including 7 evolving from WS/IS and 12 from nonsyndromic generalized, focal, or undetermined epilepsies. Evolution to LGS took a median of 1.9years. LGS developed in 13% of infants, including 9% of those who did not present initially with WS/IS. DEEs account for disproportionate amounts of pharmacoresistance, disability, and early mortality. LGS often has a window between initial presentation and full expression. LGS should become targeted for early detection and prevention.

Diagnosis switching and outcomes in a cohort of patients with potential epilepsy with myoclonic-atonic seizures

IntroductionThere is overlap in the electroclinical features of many childhood epilepsy syndromes, especially those presenting with multiple seizure types, such as epilepsy with myoclonic-atonic seizures (EMAS) and Lennox-Gastaut syndrome (LGS). This study aimed to determine the frequency of diagnosis switching and the factors influencing epilepsy syndrome diagnosis in a cohort of children with possible EMAS, as well as to explore the relationship between epilepsy syndrome diagnoses, key electroclinical features, and clinically relevant outcomes. MethodsThis is a cross-sectional retrospective chart review of children treated at the Children’s Hospital of Colorado with a potential diagnosis of EMAS. ResultsThere were 77 patients that met eligibility criteria, including 39% (n = 30) with an initial diagnosis of EMAS and 74% (n = 57) with a final diagnosis of EMAS. On average, for the 65% of patients who received more than one epilepsy diagnosis, the first, second, and third diagnoses were received within one year, three years, and ten years after epilepsy onset, respectively. Final diagnosis was significantly related to obtaining at least a six-month period of seizure freedom, p = 0.03. Classic LGS traits, including paroxysmal fast activity, slow spike-and-wave, and tonic seizures were present in 50% of the overall cohort, although a minority of these patients had a final diagnosis of LGS. However, the presence of more LGS traits was associated with a higher likelihood of ongoing seizures. Adjusted for age of epilepsy onset, seizure freedom was half as likely for every additional LGS trait observed (0.49[0.31, 0.77], p = 0.002). ConclusionCurrent epilepsy syndrome classification has reduced applicability due to overlapping features. This results in diagnosis switching and limited prognostic value for patients with an overlapping clinical phenotype. Future studies should attempt to stratify patients based not only on epilepsy syndrome diagnosis, but also on the presence of various electroclinical traits to more accurately predict outcome.

Incidence of dementia in patients with adult-onset epilepsy of unknown causes

Epilepsy is generally considered to occur most commonly in childhood; however, several epidemiological studies confirmed that its occurrence increases from middle age [ [1] Hauser W.A. Seizure disorders: the changes with age. Epilepsia. 1992; 33: S6-S14 Crossref PubMed Scopus (344) Google Scholar , [2] Olafsson E. Ludvigsson P. Gudmundsson G. Hesdorffer D. Kjartansson O. Hauser W.A. Incidence of unprovoked seizures and epilepsy in Iceland and assessment of the epilepsy syndrome classification: a prospective study. Lancet Neurol. 2005; 4: 627-634 Abstract Full Text Full Text PDF PubMed Scopus (271) Google Scholar ], and is the third most common neurological disease affecting the elderly, following dementia and cerebrovascular disease (CVD) [ [3] Brodie M.J. Kwan P. Epilepsy in elderly people. BMJ. 2005; 331: 1317-1322 Crossref PubMed Scopus (141) Google Scholar , [4] Werhahn K.J. Epilepsy in the elderly. Dtsch Arztebl Int. 2009; 106: 135-142 PubMed Google Scholar ]. These diseases interact with each other in later life. The leading etiology of elderly-onset epilepsy is CVD [ [5] Hauser W.A. Rowan A.J. Ramsay R.E. Epidemiology of Seizures and Epilepsy in the Elderly. Butterworth-Heinemann, Boston1997: 7-18 Google Scholar , [6] Wallace H. Shorvon S. Tallis R. Age-specific incidence and prevalence rates of treated epilepsy in an unselected population of 2,052,922, and age-specific fertility rates of women with epilepsy. Lancet. 1998; 352: 1970-1973 Abstract Full Text Full Text PDF PubMed Scopus (322) Google Scholar ], and CVD is a major risk factor for dementia with neurodegenerative disease, especially Alzheimer's disease (AD) [ [7] Petrovitch H. Ross G.W. Steinhorn S.C. Abott R.D. Markesbery W. Davis D. et al. AD lesions and infarcts in demented and non-demented Japanese-American men. Ann. Neurol. 2005; 57: 98-103 Crossref PubMed Scopus (202) Google Scholar , [8] J. Obrien R. Vascular dementia: atherosclerosis, cognition and Alzheimer's disease. Curr. Alzheimer Res. 2011; 8: 341-344 Crossref PubMed Scopus (13) Google Scholar ]. Adult-onset epilepsy is considered as a consequence of structural damage of the central nervous system (CNS), and the existence of AD, a typical neurodegenerative disease, also increases the occurrence of epilepsy [ [9] Scarmeas N. Honig L.S. Choi H. Cantero J. Brandt J. Blacker D. et al. Seizures in Alzheimer disease: who, when, and how common?. Arch. Neurol. 2009; 66: 992-997 Crossref PubMed Scopus (221) Google Scholar ]. This clinical finding is supported by several basic studies using a transgenic mouse model of AD, which demonstrated that deposited amyloid-β (Aβ) causes epileptiform discharges in the cortex, nonconvulsive seizures, and cognitive dysfunction [ [10] Palop J.J. Chin J. Roberson E.D. Wang J. Thwin M.T. Bien-Ly N. et al. Compensatory remodering of inhibitory hippocampal circuits in mouse models in Alzheimer's disease. Neuron. 2007; 55: 697-711 Abstract Full Text Full Text PDF PubMed Scopus (1121) Google Scholar , [11] Huang Y. Mucke L. Alzheimer mechanisms and therapeutic strategies. Cell. 2012; 148: 1204-1222 Abstract Full Text Full Text PDF PubMed Scopus (1358) Google Scholar ]. Taking into account the evidence that Aβ deposition starts >10 years before clinical signs of AD appear [ [12] Villemagne V.L. Burnham S. Bourgeat P. Amyloid β deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer's disease: a prospective cohort study. Lancet Neurol. 2013; 12: 357-367 Abstract Full Text Full Text PDF PubMed Scopus (1410) Google Scholar ], epilepsy may develop earlier than AD. To test this hypothesis, we retrospectively studied the occurrence of AD in patients with adult-onset epilepsy of unknown causes to elucidate whether these patients are more likely to develop AD than control patients. Moreover, to determine whether an atherosclerotic factor affects the occurrence of AD, we also investigated the occurrence of CVD in both groups.