The relationship between <scp>d</scp>‐beta‐hydroxybutyrate blood concentrations and seizure control in children treated with the ketogenic diet for medically intractable epilepsy
Bibliographic record
Abstract
Objective: The ketogenic diet (KD) is a proven treatment for drug-resistant (DR) seizures in children and adolescents. However, the relationship between seizure control and the most commonly measured metabolite of the diet, the ketone body d-beta-hydroxybutyrate (D-BHB), is controversial. This study was performed to clarify the relationship because specific ketone bodies may be useful as biomarkers of diet efficacy. Methods: Families of children with DR seizures were approached for participation in this open-label, prospective study when they were referred for the KD at two western Canadian children's hospitals. Inclusion criteria included documentation of DR seizures without exclusion based on age, sex, seizure, or syndrome type. Patients were excluded if they were referred for treatment of a metabolic disorder independent of seizures. Seizures were quantified via parental report and standardized as seizure frequency per 28 days. Epilepsy syndromes were identified on the basis of the medical record. Blood D-BHB was determined by tandem mass spectrometry. Results: A total of 23 patients were recruited from both sites. Data from five individuals were excluded because these seizures occurred in clusters, leaving 18 patients for the primary analysis. In the latter group, a clear positive correlation was present between measures of seizure frequency and D-BHB concentrations. However, this failed to reach statistical significance, likely because of the relatively small numbers. Significance: A trend clearly exists between seizure frequency and D-BHB levels, so we should not be dissuaded by the lack of statistical significance because it possibly results from methodological techniques, especially sample size. These results call for a larger prospective study in which seizure frequency is assessed at the point of care in a standardized fashion so as to determine whether D-BHB can be used as a reliable biomarker of KD efficacy.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".