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Electroclinical features of absence seizures in childhood absence epilepsy

2006· article· en· W2064113649 on OpenAlexaff
Lynette G. Sadleir, K Farrell, Scott C. Smith, Mary Connolly, Ingrid E. Scheffer

Bibliographic record

VenueNeurology · 2006
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsBC Children's Hospital
Fundersnot available
KeywordsIctalChildhood absence epilepsyEpilepsyElectroencephalographySpike-and-wavePediatricsAudiologyMedicineSeizure typesPsychologyAnesthesiaNeuroscience

Abstract

fetched live from OpenAlex

OBJECTIVE: To accurately define the electroclinical features of absence seizures in children with newly diagnosed, untreated childhood absence epilepsy (CAE). METHODS: The authors searched an EEG database for absence seizures in normal children with new onset untreated absence epilepsy. Seventy consecutive children were classified into IGE syndromes. The clinical and EEG features of the seizures in the children with CAE were analyzed using video-EEG recordings. RESULTS: The authors analyzed 339 absence seizures in 47 children with CAE. The average seizure duration was 9.4 seconds and clinical features consisted of arrest of activity, loss of awareness, staring, and 3-Hz eyelid movements, but there was individual variation. Ictal EEG predominantly showed regular 3-Hz generalized spike and wave (GSW) with one or two spikes per wave; however, disorganization of discharges was common and three or more spikes per wave occurred rarely. Postictal slowing was frequent. Interictal abnormalities included fragments of GSW, posterior bilateral delta activity, and focal discharges. Although all 47 children met the current criteria for CAE, only 5 fulfilled the recently proposed criteria for CAE. CONCLUSION: The heterogeneous nature of each clinical and EEG feature of untreated absence seizures is of critical importance when determining criteria for childhood absence epilepsy.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.385

Codex and Gemma teacher scores by category

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

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 head0.011
GPT teacher head0.296
Teacher spread0.285 · 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 teacher head, 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

Citations183
Published2006
Admission routes1
Has abstractyes

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