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Record W2832830805 · doi:10.20453/rnp.v81i2.3337

Síndrome de Lennox Gastaut. Aproximación diagnóstica y avances terapéuticos: Fármacos antiepilépticos, Canabidiol y otras alternativas.

2018· article· es· W2832830805 on OpenAlexaff
Manuel L. Herrera, Jorge G. Burneo

Bibliographic record

VenueRevista de Neuro-Psiquiatría · 2018
Typearticle
Languagees
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsWestern University
Fundersnot available
KeywordsHumanitiesMedicinePhilosophy

Abstract

fetched live from OpenAlex

El Síndrome de Lennox Gastaut es una encefalopatía epiléptica catastrófica de inicio en la infancia con características electro-clínicas definidas de la siguiente manera: 1) presencia de múltiples tipos de crisis epilépticas especialmente tónicas; 2) deterioro cognitivo asociado a cambios conductuales; 3) presencia de complejos punta-onda lenta generalizados en el electroencefalograma (EEG) y paroxismos generalizados de actividad rítmica rápida durante el sueño. Su etiología puede ser estructural o genética (antes denominadas sintomáticas y criptogénicas, respectivamente). El diagnóstico inicial puede ser difícil ya que con frecuencia no se identifican todos los criterios al comienzo del cuadro y el diferencial considera otros síndromes epilépticos de inicio en la infancia, tales como las epilepsias mioclónicas. El tratamiento es muy complejo, se carece de guías definidas de práctica clínica, por lo cual la experiencia de expertos es relevante. Se sugiere inicio de medicación con valproato. Lamotrigina, felbamato, topiramato, rufinamida y clobazam son los fármacos de elección de segunda línea aprobados por la Administración Federal de Alimentos y Drogas de los Estados Unidos. (FDA). El manejo quirúrgico incluye cirugía resectiva y callosotomía total o parcial. Otras alternativas son estimulación del Nervio Vago, dieta cetogénica, estimulación cerebral profunda y el uso médico de cannabis.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.538
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.020
GPT teacher head0.326
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; both teacher heads agree on what is shown here.

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

Citations4
Published2018
Admission routes1
Has abstractyes

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