MétaCan
Menu
Back to cohort
Record W2592509339 · doi:10.1111/epi.13709

<scp>ILAE</scp> classification of the epilepsies: Position paper of the <scp>ILAE</scp> Commission for Classification and Terminology

2017· article· en· W2592509339 on OpenAlexafffund
Ingrid E. Scheffer, Samuel F. Berkovic, Giuseppe Capovilla, Mary Connolly, Jacqueline A. French, Laura Maria de Figueiredo Ferreira Guilhoto, Édouard Hirsch, Gary W. Mathern, Solomon L. Moshé, Douglas R. Nordli, Emilio Perucca, Torbjörn Tomson, Samuel Wiebe, Sameer M. Zuberi

Bibliographic record

VenueEpilepsia · 2017
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsUniversity of CalgaryBC Children's HospitalUniversity of British Columbia
FundersCilagUCB PharmaNational Health and Medical Research CouncilMedical Research CouncilCanadian Institutes of Health ResearchUniversity of California, Los AngelesSun PharmaUniversidade Católica de BrasíliaFundação BialEisaiEpilepsy Research UKNeuroPaceNational Institutes of HealthMylanSupernus PharmaceuticalsZynerba PharmaceuticalsUpsher-SmithDivision of Arctic SciencesSage TherapeuticsEpilepsiatutkimussäätiöDravet Syndrome UKZogenixAlva FoundationLundbeckfondenU.S. Department of DefenseYorkhill Children’s CharityGW PharmaceuticalsSanofiCitizens United for Research in EpilepsyNovartisAcorda TherapeuticsStockholms Läns LandstingTakeda Pharmaceuticals U.S.A.PfizerHumanities Research Center, Rice UniversityUltragenyx PharmaceuticalGlaxoSmithKlineVertex PharmaceuticalsMarch of Dimes FoundationNational Institute of Neurological Disorders and StrokeCURE Childhood CancerH. Lundbeck A/SSunovion
KeywordsEpilepsyTerminologyEtiologyMedicineEpilepsy syndromesGeneralized epilepsyPediatricsIntensive care medicinePsychiatry

Abstract

fetched live from OpenAlex

The International League Against Epilepsy (ILAE) Classification of the Epilepsies has been updated to reflect our gain in understanding of the epilepsies and their underlying mechanisms following the major scientific advances that have taken place since the last ratified classification in 1989. As a critical tool for the practicing clinician, epilepsy classification must be relevant and dynamic to changes in thinking, yet robust and translatable to all areas of the globe. Its primary purpose is for diagnosis of patients, but it is also critical for epilepsy research, development of antiepileptic therapies, and communication around the world. The new classification originates from a draft document submitted for public comments in 2013, which was revised to incorporate extensive feedback from the international epilepsy community over several rounds of consultation. It presents three levels, starting with seizure type, where it assumes that the patient is having epileptic seizures as defined by the new 2017 ILAE Seizure Classification. After diagnosis of the seizure type, the next step is diagnosis of epilepsy type, including focal epilepsy, generalized epilepsy, combined generalized, and focal epilepsy, and also an unknown epilepsy group. The third level is that of epilepsy syndrome, where a specific syndromic diagnosis can be made. The new classification incorporates etiology along each stage, emphasizing the need to consider etiology at each step of diagnosis, as it often carries significant treatment implications. Etiology is broken into six subgroups, selected because of their potential therapeutic consequences. New terminology is introduced such as developmental and epileptic encephalopathy. The term benign is replaced by the terms self-limited and pharmacoresponsive, to be used where appropriate. It is hoped that this new framework will assist in improving epilepsy care and research in the 21st century.

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)0.011
metaresearch head score (Gemma)0.050
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 score0.039
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.050
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0060.007
Science and technology studies0.0030.003
Scholarly communication0.0070.005
Open science0.0030.004
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0310.036

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 head0.048
GPT teacher head0.325
Teacher spread0.277 · 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

Citations4,881
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueEpilepsiaSame topicEpilepsy research and treatmentFrench-language works237,207