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Record W3000354699 · doi:10.1684/epd.2019.1116

Benign spasms of infancy: a mimicker of infantile epileptic disorders*

2019· article· en· W3000354699 on OpenAlexaff
Jamie Ghossein, Daniela Pohl

Bibliographic record

VenueEpileptic Disorders · 2019
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of Ottawa
Fundersnot available
KeywordsMedicinePediatricsEpilepsyPsychiatry

Abstract

fetched live from OpenAlex

Benign spasms of infancy (BSI), previously described as benign non-epileptic infantile spasms or benign myoclonus of early infancy, are non-epileptic movements manifesting during the first year of life and spontaneously resolving in the second year of life. BSI are characterized by spasms typically lasting 1-2 seconds, involving, to varying degrees, the head, neck, trunk, shoulders and upper extremities. Ictal and interictal EEG recordings are normal. BSI are not associated with developmental regression and do not require treatment. Distinction between BSI and infantile epileptic disorders, such as epileptic spasms or myoclonic epilepsy of infancy, can be challenging given the clinical similarities. Moreover, interictal EEGs can be normal in all conditions. Epileptic spasms and myoclonic epilepsy require timely treatment to improve neurodevelopmental outcomes. We describe a six-month-old infant presenting with spasm-like movements. His paroxysms as well as a positive family history for epileptic spasms were in keeping with a likely diagnosis of West syndrome. Surprisingly, ictal video-EEG did not reveal epileptiform activity, and suggested a diagnosis of BSI. We emphasize that ictal video-EEG is the gold standard for classification of infantile paroxysms as epileptic or non-epileptic, thereby avoiding over-treatment for BSI and facilitating timely targeted treatment of infantile epilepsies. [Published with video sequences].

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.006
GPT teacher head0.260
Teacher spread0.254 · 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 designCase report
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

Citations12
Published2019
Admission routes1
Has abstractyes

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