Abbreviated mycophenolic acid AUC from C0, C1, C2, and C4 is preferable in children after renal transplantation on mycophenolate mofetil and tacrolimus therapy
Bibliographic record
Abstract
In order to allow a similar algorithm to be used for both adults and children on tacrolimus-based and mycophenolate mofetil [MMF, a pro-drug for mycophenolic acid (MPA)]-based immunosuppression, a limited sampling technique from the trough level (C0) and the levels 30 min (C0.5) and 2 h (C2) after intake was to be developed from MPA area under the time-concentration curves (AUC). We retrospectively analyzed 49 full ten-point pharmacokinetic (PK) profiles from 29 pediatric patients on MMF and tacrolimus. We used stepwise multiple regression analysis to calculate limited sampling approaches. Agreement with the AUC was tested by means of Bland and Altman analysis. The correlation between AUC and pre-dose trough concentration was r(2)=0.5188 ( P<0.0001) and between AUC and post-dose trough concentration r(2)=0.6924 ( P<0.0001). The next best correlations were with 2 h (C2, r(2)=0.6711, P<0.0001), 4 h (C4, r(2)=0.6411, P<0.0001), 1.5 h (C1.5, r(2)=0.6344, P<0.0001), and 6 h (C6, r(2)=0.6219, P<0.0001). Three-point estimates at C0, C0.5, and C2 resulted in an acceptable correlation between predicted AUC and AUC from the full profile when we used the formula AUC = 10.01391+3.94791xC0+3.24253xC0.5+1.0108xC2, Pearson's r=0.8996, 95% confidence interval 0.8277-0.9424. However, even better results could be obtained when we used AUC = 8.217+3.163xC0+0.994xC1+1.334xC2+4.183xC4, Pearson's r=0.9456, 95% confidence interval 0.9051-0.9691. Bland and Altman analysis revealed good agreement between AUC predicted from C0, C0.5, and C2 and AUC from the full profile, but was inferior to the four-point approach. Also, the previously reported formula derived for adults was not usable in these patients. A special formula must be used for children. The AUC of MPA can be predicted by limited sampling including C0, C0.5, and C2, while an approach using C0, C1, C2, and C4 is preferable.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".