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Record W2607001943 · doi:10.1017/cjn.2015.62

The long-term outcome of children with refractory epilepsy after a vagal nerve stimulator implantation: CHU Sainte-Justine experience

2015· article· en· W2607001943 on OpenAlexvenueaboutno aff
ML Kaseka, LS Carmant, E Desplats, Louis Crevier, Philippe Major, Paola Diadori, Anne Lortie, C Mercier, Lionel Carmant

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2015
Typearticle
Languageen
FieldNeuroscience
TopicVagus Nerve Stimulation Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRefractory (planetary science)EpilepsyAnesthesiaSurgery

Abstract

fetched live from OpenAlex

Background: Debate persists in Canada about the cost and benefit of vagal nerve stimulation in patients with refractory epilepsy. The aim of our study was to evaluate the impact of a vagal nerve stimulator on the seizure frequency and the admission rate of children with refractory epilepsies over five years of follow-up. Methods: 52 patients were implanted between 2000-2013. Of these, 37 were followed at CHU Sainte-Justine and 21 kept seizure diaries. Seizure frequency was compared to the baseline at 6 months, 12 months, 24 months and 60 months of follow up using a multivariate ANOVA analysis. The hospitalization rate was calculated as the mean difference between the number of hospitalizations prior to and after the implantation. Results: Seizure frequency decreased by 58% at 6 months, by 61% at 12 months, by 53% at 24 months and by 63% at 60 months of follow up respectively compared to the baseline (p<0.001). The hospitalization rate decreased by 50.87% after surgery (p<0.001). Conclusion: In our population, vagal nerve stimulation has a sustained impact on seizure frequency and hospitalization rates. This supports previous data from our group and others on cost-effectiveness of the technique in children with refractory epilepsy.

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 categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0030.012
Scholarly communication0.0010.001
Open science0.0030.000
Research integrity0.0000.001
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 head0.079
GPT teacher head0.340
Teacher spread0.261 · 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

Citations0
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences NeurologiquesSame topicVagus Nerve Stimulation ResearchFrench-language works237,207