DIFFERENCES IN PHARMACOKINETIC PROFILES BETWEEN LONG-TERM HEART TRANSPLANT PATIENTS RECEIVING EITHER TACROLIMUS OR CYCLOSPORINE MICROEMULSION AND MYCOPHENOLATE MOFETIL MAINTENANCE IMMUNOSUPPRESSION
Bibliographic record
Abstract
P626 Therapeutic drug monitoring (TDM) of tacrolimus (Tacro) is based on trough level concentration (C0). However, either acute rejection or renal dysfunction may be observed in the presence of “therapeutic” C0. TDM of mycophenolate mofetil (MMF) is mostly based on side-effects and not on mycophenolic acid (MPA) C0. We have previously described that cyclosporine microemulsion (CsA) C2 is the best surrogate (r2=0.87) of the CsA AUC0-12 hr and that MPA C6provides the best, although weak correlation (r2=0.60) with the AUC0-12 hr. Purpose: To determine if there are differences in the pharmacokinetic profiles in long-term heart transplant (Tx) patients (pts) receiving either Tacro or CsA and MMF maintenance immunosuppression. Methods: We initially studied 14 long-term heart Tx pts (57±13 yrs) on maintenance CsA and MMF and more recently, 9 long-term heart Tx pts (54±12 yrs) on Tacro and MMF. All the pts were stable, >1-yr post-Tx. The AUC0-12 hr was constructed from 8 blood samples per pt. Results: Results are shown in the tables.FigureFigureConclusion: Our results suggest that in long-term heart Tx pts, Tacro C1, C2, C3, C4, C6 and C8 are superior time point predictors of Tacro AUC0-12 hr compared to Tacro C0. In Tacro-treated pts, MPA C4, C6 and C8 are superior time point predictors of MPA AUC0-12 hr compared to MPA C0. Prospective studies should determine the effectiveness of Tacro and MPA TDM with Tacro and MPA C4 respectively. In CsA-treated heart Tx pts, CsA TDM should be performed with C2. Based on the poor correlation between MPA single time-points and the AUC0-12 hr, MMF TDM may be clinically irrelevant in CsA-treated heart Tx pts.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".