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Record W2800169682 · doi:10.14740/jnr.v8i1-2.436

The Rate of Obesity in Psychogenic Non-Epileptic Seizures: A Retrospective Study

2018· article· en· W2800169682 on OpenAlexvenueno aff
Abuhuziefa Abubakr, Ilse Wambacq

Bibliographic record

VenueJournal of Neurology Research · 2018
Typearticle
Languageen
FieldMedicine
TopicNeurological and metabolic disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEpilepsyPsychogenic diseaseOverweightObesityBody mass indexPediatricsRetrospective cohort studyPopulationCohortInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Background: Obesity is common in US population at a rate of 60%. Similarly, the rate of overweight/obesity in epilepsy patients was significantly higher; however, there were no reports in patients with psychogenic non-epileptic seizures (PNESs). Methods: We retrospectively reviewed all the records of patients admitted to the epilepsy monitoring unit with the diagnosis of PNES. Body mass index (BMI) was calculated and compared to the reported rate of obesity in epilepsy patients (55.2-72%). Results: The rate of overweight/obese in our cohort with PNES is 69.3%, similar to what has been reported in the epilepsy population. We did not find any correlation between frequency of seizures, duration of symptom onset or antiepileptic drugs (AEDs) with positive effect on weight and the current rate of obesity in PNES patients. Conclusion: We concluded that overweight/obesity in PNES is similar to the reported rate of the epilepsy patients and may reflect the overall trend of obesity in the general population. J Neurol Res. 2018;8(1-2):1-3 doi: https://doi.org/10.14740/jnr436w

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)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.021
Threshold uncertainty score0.693

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.062
GPT teacher head0.423
Teacher spread0.362 · 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.

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

Citations0
Published2018
Admission routes1
Has abstractyes

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