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Record W2605063596 · doi:10.1111/epi.13730

Derivation and initial validation of a surgical grading scale for the preliminary evaluation of adult patients with drug‐resistant focal epilepsy

2017· article· en· W2605063596 on OpenAlexafffund
Patricia Dugan, Chad Carlson, Nathalie Jetté, Samuel Wiebe, Marjorie Bunch, Ruben Kuzniecky, Jacqueline A. French

Bibliographic record

VenueEpilepsia · 2017
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsUniversity of Calgary
FundersNational Institute of Neurological Disorders and StrokeCanadian Institutes of Health ResearchUniversidade Católica de BrasíliaLundbeckfondenUniversity of CalgaryPfizer
KeywordsEpilepsy surgeryConcordanceEpilepsySemiologyMagnetic resonance imagingMedicineDrug Resistant EpilepsyGrading scaleGrading (engineering)SurgeryRadiologyInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: Presently, there is no simple method at initial presentation for identifying a patient's likelihood of progressing to surgery and a favorable outcome. The Epilepsy Surgery Grading Scale (ESGS) is a three-tier empirically derived mathematical scale with five categories: magnetic resonance imaging (MRI), electroencephalography (EEG), concordance (between MRI and EEG), semiology, and IQ designed to stratify patients with drug-resistant focal epilepsy based on their likelihood of proceeding to resective epilepsy surgery and achieving seizure freedom. METHODS: In this cross-sectional study, we abstracted data from the charts of all patients admitted to the New York University Langone Medical Center (NYULMC) for presurgical evaluation or presented in surgical multidisciplinary conference (MDC) at the NYU Comprehensive Epilepsy Center (CEC) from 1/1/2007 to 7/31/2008 with focal epilepsy, who met minimal criteria for treatment resistance. We classified patients into ESGS Grade 1 (most favorable), Grade 2 (intermediate), and Grade 3 (least favorable candidates). Three cohorts were evaluated: all patients, patients presented in MDC, and patients who had resective surgery. The primary outcome measure was proceeding to surgery and seizure freedom. RESULTS: Four hundred seven patients met eligibility criteria; 200 (49.1%) were presented in MDC and 113 (27.8%) underwent surgery. A significant difference was observed between Grades 1 and 3, Grades 1 and 2, and Grades 2 and 3 for all presurgical patients, and those presented in MDC, with Grade 1 patients having the highest likelihood of both having surgery and becoming seizure-free. There was no difference between Grades 1 and 2 among patients who had resective surgery. SIGNIFICANCE: These results demonstrate that by systematically using basic information available during initial assessment, patients with drug-resistant epilepsy may be successfully stratified into clinically meaningful groups with varied prognosis. The ESGS may improve communication, facilitate decision making and early referral to a CEC, and allow patients and physicians to better manage expectations.

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)0.004
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.338
Teacher spread0.305 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations34
Published2017
Admission routes2
Has abstractyes

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