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Record W3016722195 · doi:10.1684/epd.2020.1149

MoCA as a cognitive assessment tool for absence status epilepticus

2020· article· en· W3016722195 on OpenAlexaboutno aff
Sofia Grenho Rodrigues, Raquel Gil‐Gouveia, Carla Bentes

Bibliographic record

VenueEpileptic Disorders · 2020
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsStatus epilepticusMontreal Cognitive AssessmentCognitionElectroencephalographyMedicineAudiologyEpilepsyPsychologyCognitive impairmentPsychiatry

Abstract

fetched live from OpenAlex

De novo absence status is clinically characterized by a confusional syndrome and neurophysiologically by the presence of periodic spike/polyspike-and-wave discharges on EEG. The treatment should be started promptly, and fast recovery is usually seen. However, cognitive symptoms can be very difficult to detect, and no consensus exists on how cognitive improvement can be clinically monitored. We report a patient with absence status epilepticus, whose therapeutic response was monitored neurophysiologically with EEG and clinically with a cognitive test; the Montreal Cognitive Assessment (MoCA). Based on this case report, we describe the use of the MoCA for monitoring cognitive function in a patient with absence status epilepticus. MoCA was evaluated on three occasions, with a total score ranging from 9, before treatment, to 23, when an EEG with no epileptiform discharges was obtained. We suggest that MoCA may be a useful tool to monitor cognitive improvement in absence status epilepticus.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.021
GPT teacher head0.340
Teacher spread0.319 · 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 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
Published2020
Admission routes1
Has abstractyes

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