Real-World Evidence of Factors Affecting Cannabidiol Exposure in Children with Drug-Resistant Developmental and Epileptic Encephalopathies
Bibliographic record
Abstract
The identification of factors that affect cannabidiol (CBD) systemic exposure may aid in optimizing treatment efficacy and safety in clinical practice. In this study, we aimed to correlate CBD plasma concentrations at a steady state to demographic, clinical, and pharmacological characteristics as well as seizure frequency after the administration of a purified CBD oil solution in a real-world setting of children with drug-resistant developmental and epileptic encephalopathies (DEEs). Patients receiving oral CBD pharmaceutical products at maintenance were enrolled. Venous blood samples were drawn before the CBD morning dose, 12 h apart from the last evening dose (C0 or CBD trough concentration). A linear mixed-effect analysis was implemented to assess the correlation between C0 and clinical, laboratory, pharmacological, and lifestyle factors. Fifteen females and seven males with a median age of 12.8 years (ranging between 4.7 and 17.2) were included. The median CBD dose was 8.8 mg/kg/day (ranging between 2.6 and 22.5), and the CBD C0 median (range) was 48.2 ng/mL (3.5–366.3). The multivariate model showed a 109.6% increase in CBD C0 in patients with concomitant levothyroxine (β = 0.74 ± 0.1649, p < 0.001), 56.8% with food (β = 0.45 ± 0.1550, p < 0.01), and 116.0% after intake of a ketogenic diet (β = 0.77 ± 0.3141, p < 0.05). All patients included were responders without evidence of an association between C0 and response status. In children with DEEs, systemic concentrations of CBD may be significantly increased when co-administered with levothyroxine, food, or a ketogenic diet.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".