P.044 Quality of life in children with epilepsy treated with the low glycemic index diet – a pilot study
Bibliographic record
Abstract
Background: The classic ketogenic diet is the main non-pharmacological treatment for refractory epilepsy; however, adherence is often challenging. The low glycemic index diet (LGID) is less strict, almost equally effective, and associated with improved adherence. Little is known about the quality of life of children treated with LGID. The objective of this study was to explore changes in the quality of life of children with epilepsy transitioning to the LGID. Methods: Patients on LGID and their parents filled out Pediatric Quality of Life Epilepsy Module questionnaires; one while being on the LGID, and one retrospectively for the time prior to starting the LGID. Results: Data was collected from five children ages 3-13 and their parents. Complete seizure control was seen in two children, >50% seizure reduction in one, and no change in two children. Parental reported quality of life while on the LGID increased with two participants but decreased in all child self reports. Conclusions: Although the LGID led to improved seizure control in three out of five patients, the child-reported quality of life decreased in all children. Larger prospective studies are warranted to reliably assess the impact of the LGID on the quality of life in children with epilepsy.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".