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Record W2767649791 · doi:10.33588/rn.6506.2017188

Barreras de acceso a la cirugía de la epilepsia: revisión de la bibliografía

2017· article· es· W2767649791 on OpenAlexaff
Lady Diana Ladino, Vanessa Benjumea‐Cuartas, J Vargas-Osorio, Lyda Viviana Villamil-Osorio, Laura E. Hernández‐Vanegas, José Francisco Téllez‐Zenteno

Bibliographic record

VenueRevista de Neurología · 2017
Typearticle
Languagees
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsRoyal University Hospital
Fundersnot available
KeywordsMedicineEpilepsy surgeryEpilepsyPsychiatry

Abstract

fetched live from OpenAlex

Drug-resistant epilepsy, a chronic condition with long-term consequences can be treated with surgery. The efficacy and safety of surgery for temporal lobe epilepsy have been established through a large number of retrospective and prospective cohort studies and two randomized controlled clinical trials. Despite the excellent outcomes reported after surgery, the literature suggests that this procedure is an underutilized treatment. While evidence is lacking as to why epilepsy surgery is underused, cited reasons include: failure of primary care physicians and neurologists to provide information and identify patients who could be referred for surgery; different levels of technology at various centers, resulting in different candidate selection strategies; the belief that epilepsy surgery is a risky procedure and that it should be only viewed as the last option; patient preference to avoid surgery; parents wanting to wait until their child is old enough to participate in the decision-making process regarding surgery; unwillingness of insurers to cover the expenses associated with presurgical evaluations or lack of insurance; racial and social disparities, among others. In this paper we review the available epidemiological data about lack of utilization of epilepsy surgery.

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)0.005
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.286
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.000
Open science0.0010.001
Research integrity0.0010.002
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 head0.017
GPT teacher head0.365
Teacher spread0.347 · 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 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

Citations5
Published2017
Admission routes1
Has abstractyes

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