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Record W2169126479 · doi:10.1177/0883073811413129

Treatment of Infantile Spasms

2011· review· en· W2169126479 on OpenAlexaff
Carl E. Stafstrom, Barry G.W. Arnason, Tallie Z. Baram, Anna Catania, Miguel A. Cortez, Tracy A. Glauser, Michael R. Pranzatelli, Raili Riikonen, Michael A. Rogawski, Shlomo Shinnar, John W. Swann

Bibliographic record

VenueJournal of Child Neurology · 2011
Typereview
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineAdrenocorticotropic hormoneWest SyndromeVigabatrinHypsarrhythmiaEpilepsyElectroencephalographyMechanism (biology)Epileptic spasmsIntensive care medicineEncephalopathyPediatricsNeurosciencePsychologyPsychiatryInternal medicineAnticonvulsantHormone

Abstract

fetched live from OpenAlex

Infantile spasms is an epileptic encephalopathy of early infancy with specific clinical and electroencephalographic (EEG) features, limited treatment options, and a poor prognosis. Efforts to develop improved treatment options have been hindered by the lack of experimental models in which to test prospective therapies. The neuropeptide adrenocorticotropic hormone (ACTH) is effective in many cases of infantile spasms, although its mechanism(s) of action is unknown. This review describes the emerging candidate mechanisms that can underlie the therapeutic effects of ACTH in infantile spasms. These mechanisms can ultimately help to improve understanding and treatment of the disease. An overview of current treatments of infantile spasms, novel conceptual and experimental approaches to infantile spasms treatment, and a perspective on remaining clinical challenges and current research questions are presented here. This summary derives from a meeting of specialists in infantile spasms clinical care and research held in New York City on June 14, 2010.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.057
GPT teacher head0.362
Teacher spread0.306 · 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
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

Citations67
Published2011
Admission routes1
Has abstractyes

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