The Rate of Obesity in Psychogenic Non-Epileptic Seizures: A Retrospective Study
Bibliographic record
Abstract
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
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".