Early Adequate Mycophenolic Acid Exposure is Associated with Less Rejection in Kidney Transplantation
Bibliographic record
Abstract
This study examines the importance of early mycophenolic acid (MPA) exposure in the cyclosporine- and mycophenolate mofetil (MMF)-treated kidney transplant population. We prospectively evaluated 94 first solitary kidney transplant patients treated with cyclosporine (Neoral), MMF, and prednisone. Basiliximab was also given to 72 recipients. MPA exposure was measured by HPLC using a limited sampling estimate of 12 h area under the curve (AUC [0-12]) within the first week. Efficacy was determined by the occurrence of acute rejection and toxicity by the need to reduce MMF doses within the first 3 months post-transplantation. Acute rejection was observed in 14 (15%) and MMF toxicity in 27 (29%). Receiver operator curve analysis shows that MPA AUC [0-12] on day 3 was predictive of efficacy (c = 0.72, p = 0.007) but not toxicity (c = 0.57, p = 0.285). A separate analysis of only patients on basiliximab shows that the MPA AUC [0-12] on day 3 was also predictive of efficacy (c = 0.80, p = 0.01). Therefore early adequate exposure to MPA by day 3 is associated with low acute rejection but cannot predict toxicity. Adequate MPA exposure is also important with basiliximab induction therapy.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".