Dataset Information

Pretreatment seizure semiology in childhood absence epilepsy.

ABSTRACT: To determine seizure semiology in children with newly diagnosed childhood absence epilepsy and to evaluate associations with short-term treatment outcomes.For participants enrolled in a multicenter, randomized, double-blind, comparative-effectiveness trial, semiologic features of pretreatment seizures were analyzed as predictors of treatment outcome at the week 16 to 20 visit.Video of 1,932 electrographic absence seizures from 416 participants was evaluated. Median seizure duration was 10.2 seconds; median time between electrographic seizure onset and clinical manifestation onset was 1.5 seconds. For individual seizures and by participant, the most common semiology features were pause/stare (seizure 95.5%, participant 99.3%), motor automatisms (60.6%, 86.1%), and eye involvement (54.9%, 76.5%). The interrater agreement for motor automatisms and eye involvement was good (72%-84%). Variability of semiology features between seizures even within participants was high. Clustering analyses revealed 4 patterns (involving the presence/absence of eye involvement and motor automatisms superimposed on the nearly ubiquitous pause/stare). Most participants experienced more than one seizure cluster pattern. No individual semiologic feature was individually predictive of short-term outcome. Seizure freedom was half as likely in participants with one or more seizure having the pattern of eye involvement without motor automatisms than in participants without this pattern.Almost all absence seizures are characterized by a pause in activity or staring, but rarely is this the only feature. Semiologic features tend to cluster, resulting in identifiable absence seizure subtypes with significant intraparticipant seizure phenomenologic heterogeneity. One seizure subtype, pause/stare and eye involvement but no motor automatisms, is specifically associated with a worse treatment outcome.

SUBMITTER: Kessler SK

PROVIDER: S-EPMC5562968 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Pretreatment seizure semiology in childhood absence epilepsy.

Kessler Sudha Kilaru SK Shinnar Shlomo S Cnaan Avital A Dlugos Dennis D Conry Joan J Hirtz Deborah G DG Hu Fengming F Liu Chunyan C Mizrahi Eli M EM Moshé Solomon L SL Clark Peggy P Glauser Tracy A TA

Neurology 20170719 7

<h4>Objective</h4>To determine seizure semiology in children with newly diagnosed childhood absence epilepsy and to evaluate associations with short-term treatment outcomes.<h4>Methods</h4>For participants enrolled in a multicenter, randomized, double-blind, comparative-effectiveness trial, semiologic features of pretreatment seizures were analyzed as predictors of treatment outcome at the week 16 to 20 visit.<h4>Results</h4>Video of 1,932 electrographic absence seizures from 416 participants wa ...[more]

PMID: 28724582

Similar Datasets

Project description:Semiology describes the evolution of symptoms and signs during epileptic seizures and contributes to the evaluation of individuals with focal drug-resistant epilepsy for curative resection. Semiology varies in complexity from elementary sensorimotor seizures arising from primary cortex to complex behaviours and automatisms emerging from distributed cerebral networks. Detailed semiology interpreted by expert epileptologists may point towards the likely site of seizure onset, but this process is subjective. No study has captured the variances in semiological localizing values in a data-driven manner to allow objective and probabilistic determinations of implicated networks and nodes. We curated an open data set from the epilepsy literature, in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, linking semiology to hierarchical brain localizations. A total of 11 230 data points were collected from 4643 patients across 309 articles, labelled using ground truths (postoperative seizure-freedom, concordance of imaging and neurophysiology, and/or invasive EEG) and a designation method that distinguished between semiologies arising from a predefined cortical region and descriptions of neuroanatomical localizations responsible for generating a particular semiology. This allowed us to mitigate temporal lobe publication bias by filtering studies that preselected patients based on prior knowledge of their seizure foci. Using this data set, we describe the probabilistic landscape of semiological localizing values as forest plots at the resolution of seven major brain regions: temporal, frontal, cingulate, parietal, occipital, insula, and hypothalamus, and five temporal subregions. We evaluated the intrinsic value of any one semiology over all other ictal manifestations. For example, epigastric auras implicated the temporal lobe with 83% probability when not accounting for the publication bias that favoured temporal lobe epilepsies. Unbiased results for a prior distribution of cortical localizations revised the prevalence of temporal lobe epilepsies from 66% to 44%. Therefore, knowledge about the presence of epigastric auras updates localization to the temporal lobe with an odds ratio (OR) of 2.4 [CI95% (1.9, 2.9); and specifically, mesial temporal structures OR: 2.8 (2.3, 2.9)], attesting the value of epigastric auras. As a further example, although head version is thought to implicate the frontal lobes, it did not add localizing value compared with the prior distribution of cortical localizations [OR: 0.9 (0.7, 1.2)]. Objectification of the localizing values of the 12 most common semiologies provides a complementary view of brain dysfunction to that of lesion-deficit mappings, as instead of linking brain regions to phenotypic-deficits, semiological phenotypes are linked back to brain sources. This work enables coupling of seizure propagation with ictal manifestations, and clinical support algorithms for localizing seizure phenotypes.

Dataset Information

Pretreatment seizure semiology in childhood absence epilepsy.

Publications

Pretreatment seizure semiology in childhood absence epilepsy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets