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Record W2966195295 · doi:10.1684/epd.2019.1058

Interictal epileptiform discharges in sleep and the role of the thalamus in Encephalopathy related to Status Epilepticus during slow Sleep

2019· article· en· W2966195295 on OpenAlexaff
Steve A. Gibbs, Lino Nobili, Péter Halász

Bibliographic record

VenueEpileptic Disorders · 2019
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsUniversité de MontréalHôpital du Sacré-Cœur de Montréal
Fundersnot available
KeywordsStatus epilepticusIctalThalamusSleep (system call)MedicineElectroencephalographyNeuroscienceAnesthesiaPsychologyEpilepsyAudiology

Abstract

fetched live from OpenAlex

EEG activation of interictal epileptiform discharges (IEDs) during NREM sleep is a well-described phenomenon that occurs in the majority of epileptic syndromes. In drug-resistant focal epilepsy, IED activation seems to be related to slow wave activity (SWA), especially during arousal fluctuations, namely phase A of the cyclic alternating pattern (CAP). Conversely, in childhood focal epileptic syndromes, including Encephalopathy related to Status Epilepticus during slow Sleep (ESES), IED activation seems primarily modulated by sleep-inducing and maintaining mechanisms as reflected by the dynamics of spindle frequency activity (SFA) rather than SWA. In this article, we will review the effect of sleep on IEDs with a particular attention on the activation and modulation of IEDs in ESES. Finally, we will discuss the role of the thalamus and cortico-thalamic circuitry in this syndrome.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.003
GPT teacher head0.222
Teacher spread0.219 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations27
Published2019
Admission routes1
Has abstractyes

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