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Record W4409708349 · doi:10.1111/epi.18338

Updated classification of epileptic seizures: Position paper of the International League Against Epilepsy

2025· article· en· W4409708349 on OpenAlexaff
Sándor Beniczky, Eugen Trinka, Elaine Wirrell, Fatema Abdulla, Raidah Albaradie, Mario Alonso‐Vanegas, Stéphane Auvin, Mamta Bhushan Singh, Hal Blumenfeld, Alicia Bogacz Fressola, Roberto Caraballo, Mar Carreño, Fernando Cendes, Augustina Charway‐Felli, Mark Cook, Dana Craiu, Birinus Ezeala‐Adikaibe, Birgit Frauscher, Jacqueline A. French, M. V. Gule, Norimichi Higurashi, Akio Ikeda, Floor E. Jansen, Barbara C. Jobst, Philippe Kahane, Nirmeen A. Kishk, Ching Soong Khoo, Kollencheri Puthenveettil Vinayan, Lieven Lagae, Kheng Seang Lim, Angélica Lizcano, Aileen McGonigal, Katerina Tanya Perez‐Gosiengfiao, Philippe Ryvlin, Nicola Specchio, Michael R. Sperling, H. Stefan, William O. Tatum, Manjari Tripathi, Elza Márcia Targas Yacubian, Samuel Wiebe, Jo M. Wilmshurst, Dong Zhou, J. Helen Cross

Bibliographic record

VenueEpilepsia · 2025
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsUniversity of Calgary
FundersUCB PharmaGreat Ormond Street Institute of Child HealthEngineering and Physical Sciences Research CouncilHORIZON EUROPE Framework ProgrammeVitafloNeuraxpharmH. Lundbeck A/SNational Institute of Neurological Disorders and StrokeUniversity of CambridgeGreat Ormond Street Hospital CharityNational Institute for Health and Care ResearchAngelini PharmaSage TherapeuticsZogenixUltragenyx PharmaceuticalSK Life ScienceInnovationsfondenMinistero della SaluteLivaNovaOno PharmaceuticalEisaiEurostarsGenentechUniversity of OxfordJazz PharmaceuticalsSanofiGW PharmaceuticalsLifeArcOtsuka PharmaceuticalEuropean Commission
KeywordsEpilepsySeizure typesPsychologySemiologyEpilepsy syndromesEpileptic seizureConsciousnessMedicineNeuroscience

Abstract

fetched live from OpenAlex

The International League Against Epilepsy (ILAE) has updated the operational classification of epileptic seizures, building upon the framework established in 2017. This revision, informed by the implementation experience, involved a working group appointed by the ILAE Executive Committee. Comprising 37 members from all ILAE regions, the group utilized a modified Delphi process, requiring a consensus threshold of more than two thirds for any proposal. Following public comments, the Executive Committee appointed seven additional experts to the revision task force to address and incorporate the issues raised, as appropriate. The updated classification maintains four main seizure classes: Focal, Generalized, Unknown (whether focal or generalized), and Unclassified. Taxonomic rules distinguish classifiers, which are considered to reflect biological classes and directly impact clinical management, from descriptors, which indicate other important seizure characteristics. Focal seizures and those of unknown origin are further classified by the patient's state of consciousness (impaired or preserved) during the seizure, defined operationally through clinical assessment of awareness and responsiveness. If the state of consciousness is undetermined, the seizure is classified under the parent term, that is, the main seizure class (focal seizure or seizure of unknown origin). Generalized seizures are grouped into absence seizures, generalized tonic-clonic seizures, and other generalized seizures, now including recognition of negative myoclonus as a seizure type. Seizures are described in the basic version as with or without observable manifestations, whereas an expanded version utilizes the chronological sequence of seizure semiology. This updated classification comprises four main classes and 21 seizure types. Special emphasis was placed on ensuring translatability into languages beyond English. Its aim is to establish a common language for all health care professionals involved in epilepsy care, from resource-limited areas to highly specialized centers, and to provide accessible terms for patients and caregivers.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.033
metaresearch head score (Gemma)0.056
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.052
Threshold uncertainty score0.177

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.056
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0130.009
Science and technology studies0.0020.003
Scholarly communication0.0070.005
Open science0.0060.005
Research integrity0.0040.010
Insufficient payload (model declined to judge)0.0040.006

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.299
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations305
Published2025
Admission routes1
Has abstractyes

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