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Record W4407684716 · doi:10.1016/j.brs.2025.02.010

Long-term outcomes of vagus nerve stimulation in children with drug resistant epilepsy are driven by early benefit

2025· letter· en· W4407684716 on OpenAlexaff
Karim Mithani, Farbod Niazi, Hosni Abu Alhasan, Hrishikesh Suresh, Leeor Yefet, Ivanna Yau, Lyndsey McRae, James T. Rutka, Ayako Ochi, Hiroshi Otsubo, Elizabeth Donner, Vann Chau, Puneet Jain, George M. Ibrahim

Bibliographic record

VenueBrain stimulation · 2025
Typeletter
Languageen
FieldNeuroscience
TopicVagus Nerve Stimulation Research
Canadian institutionsSickKids FoundationUniversité de MontréalHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsVagus nerve stimulationEpilepsyDrug Resistant EpilepsyStimulationMedicineTerm (time)DrugAnesthesiaVagus nerveNeurosciencePsychologyPharmacologyInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Children with drug-resistant epilepsy (DRE) are at risk of significant morbidity and mortality [1]. Patients who are ineligible for resective procedures may benefit from neuromodulation-based interventions such as vagus nerve stimulation (VNS). Despite its wide popularity, outcomes after VNS remain highly variable. Approximately 56% of children undergoing VNS experience >50% reduction in seizure frequency, with up to 12% achieving seizure freedom [2].

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.029
GPT teacher head0.305
Teacher spread0.277 · 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

Citations8
Published2025
Admission routes1
Has abstractyes

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