Severity of coeliac disease and clinical management study when using a CYP3A4 metabolised medication: a phase I pharmacokinetic study
Bibliographic record
Abstract
Objective Severity of coeliac disease depends in part on the extent of small intestinal mucosa injury. Patients with the most abnormal pathology have loss of duodenal villi CYP3A4, a drug-metabolising enzyme that inactivates many drugs. These patients are hypothesised to have greater systemic concentrations of felodipine, a drug which normally has low oral bioavailability secondary to intestinal CYP3A4-mediated metabolism. It serves as a representative for a class containing many medications. Design A phase I, open-label, single-dose, pharmacokinetic study. Setting London, Ontario, Canada. Participants Patients with coeliac disease (n=47) with positive serology and healthy individuals (n=68). Main outcome measures Patients with coeliac disease—upper gastrointestinal endoscopy and oral felodipine pharmacokinetics study within a 3-week period. Healthy individuals—oral felodipine pharmacokinetics study with water and grapefruit juice. Results Coeliac stratification categories: Group A (n=15, normal), B+C (n=16, intraepithelial lymphocytosis with/without mild villous blunting) and D (n=16, moderate/severe villous blunting). Groups A, B+C and D had linear trends of increasing felodipine AUC 0–8 ; mean±SEM, 14.4±2.1, 17.6±2.8, 25.7±5.0; p<0.05) and Cmax (3.5±0.5, 4.0±0.6, 6.4±1.1; p<0.02), respectively. Healthy subjects receiving water had lower felodipine AUC 0 – 8 (11.9±0.9 vs 26.9±0.9, p=0.0001) and Cmax (2.9±0.2 vs 7.7±0.2, p=0.0001) relative to those receiving grapefruit juice. Conclusions Increased felodipine concentrations in patients with coeliac disease were most probably secondary to decreased small intestinal CYP3A4 expression. Patients with severe coeliac disease and healthy individuals with grapefruit juice had equivalently enhanced effect. Thus, patients with severe coeliac disease would probably experience similarly altered drug response, including overdose toxicity, from many important medications known to be metabolised by CYP3A4. Patients with coeliac disease with severe disease should be considered for other clinical drug management, particularly when there is the potential for serious drug toxicity.
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".