The Role of Proton Pump Inhibitors on Early Mycophenolic Acid Exposure in Kidney Transplantation: Evidence From the CLEAR Study
Bibliographic record
Abstract
INTRODUCTION: Proton pump inhibitors (PPIs) are often prescribed posttransplantation to prevent gastrointestinal complications. A series of recent studies have reported a relationship between PPI comedication and decreased mycophenolic acid (MPA) exposure. The objective of this subanalysis of the CLEAR data set was to determine the impact of PPI therapy on full MPA area under the curve exposures at Day 5 post kidney transplant. MATERIAL AND METHODS: Patients were randomized to receive either intensified dosing of mycophenolate mofetil (1.5 g twice daily on Days 1-5, then 1.0 g twice daily, n = 68) or standard dosing (1.0 g twice daily, n = 67). All recipients received tacrolimus and prednisone. RESULTS: In the modified intention-to-treat population, 57.9% of patients (73 of 126) received PPI therapy. The most frequently administered therapies were pantoprazole and omeprazole. There was no significant difference in mean MPA area under the curve at Day 5 for patients receiving PPI therapy as compared with those not receiving PPI therapy (51.3 versus 55.8 mg.h/L, P = 0.265). However, the MPA concentration-time curve analysis demonstrated a significant decrease in MPA concentrations at 2 hours and 12 hours postdose in patients receiving PPI therapy (P = 0.0009 and P = 0.034). No significant differences were identified in the 3-g arm specifically. In the multivariate model, only serum creatinine and albumin significantly predicted MPA area under the curve less than 30 mg.h/L at Day 5. DISCUSSION AND CONCLUSION: PPI therapy in combination with mycophenolate mofetil does not appear to have a significant impact on full MPA exposure. Because MPA pharmacokinetics were not significantly impacted when a 3-g, 5-day loading dose of mycophenolate mofetil was used in combination with PPI therapy, this strategy may be required for adequate MPA exposure whether or not a patient receives PPI comedication.
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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 | 0.015 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".