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Record W2943811763 · doi:10.33588/rn.6809.2018354

Cirugía en epilepsia refractaria debida a neurocisticercosis

2019· article· es· W2943811763 on OpenAlexaff
Ana Suller Martí, Alejandro Escalaya, Jorge G. Burneo

Bibliographic record

VenueRevista de Neurología · 2019
Typearticle
Languagees
FieldMedicine
TopicParasitic infections in humans and animals
Canadian institutionsWestern University
Fundersnot available
KeywordsNeurocysticercosisMedicineEpilepsyRefractory (planetary science)Temporal lobeSurgeryPediatrics

Abstract

fetched live from OpenAlex

INTRODUCTION: Neurocysticercosis is one of the most frequent causes of epilepsy worldwide, with some cases going into refractoriness. For that reason, surgical treatment should be considered, particularly lesionectomy, with or without temporal lobectomy. CASE REPORTS: From our series of patients with drug-resistant epilepsy from 2008 to 2018, we selected all cases with one or more lesions suggestive of neurocysticercosis who underwent epilepsy surgery. Three patients fulfilled the inclusion criteria, with an average age of 39.33 year-old, two were female, epilepsy onset was at a mean age of 17.33 years. One case had multiple neurocysticercosis lesions and mesial temporal sclerosis, the other two cases had single neurocysticercosis lesions in the temporal region. In all cases, the epileptogenic zone was located in the temporal lobe. One patient underwent a temporal lobectomy, while the other two underwent lesionectomy. Pathology confirmed neurocysticercosis granuloma. All three cases remain seizure free. CONCLUSION: Evaluation of patients with neurocysticercosis-related refractory epilepsy for potential surgery is indicated, as this procedure can be quite successful.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.011
GPT teacher head0.292
Teacher spread0.281 · 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 designCase report
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

Citations2
Published2019
Admission routes1
Has abstractyes

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