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Record W2166311707 · doi:10.1017/s0317167100012889

Genetic Testing of Epileptic Encephalopathies of Infancy: An Approach

2013· review· en· W2166311707 on OpenAlexaffvenue
Suvasini Sharma, Asuri N. Prasad

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2013
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Neurodevelopmental Disorders
Canadian institutionsChildren's Hospital of Western Ontario
Fundersnot available
KeywordsEpilepsyNeuroscienceGenetic testingAbnormalityBioinformaticsStatus epilepticusMedicineElectroencephalographyLissencephalyGeneBiologyGeneticsPsychiatry

Abstract

fetched live from OpenAlex

The epileptic encephalopathies of infancy are a group of disorders characterized by intractable seizures, persistent abnormality of cortical function documented on EEG, and consequently impaired neuro-developmental outcomes. The etiologies vary and include; structural brain malformations, acquired brain insults, and inborn errors of metabolism in the majority of the affected patients. In a proportion of these cases no obvious etiology is identifiable on investigation. Recent advances in molecular diagnostics have led to the discovery of a number of gene defects that may be causal in many epileptic encephalopathies. Identification of the causative mutation is important for prognostic and genetic counseling, and may also carry treatment implications. The recently described genes include; Cyclin-Dependent Kinase-Like 5 gene (CDKL5), Protocadherin 19 (PCDH19), Sodium channel neuronal type 1a subunit gene (SCN1A), Aristaless-Related Homeobox Gene (ARX), and Syntaxin binding protein 1 gene (STXBP1), amongst others. Distinct electro-clinical syndromes are increasingly being identified amongst patients carrying the various mutations. In this review, we outline the approach to clinical evaluation and genetic testing of epileptic encephalopathies in infancy.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.723
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.006
Scholarly communication0.0000.000
Open science0.0030.000
Research integrity0.0000.001
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 head0.056
GPT teacher head0.284
Teacher spread0.228 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations26
Published2013
Admission routes2
Has abstractyes

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