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Record W2333368946 · doi:10.1097/ftd.0000000000000021

Similar MPA Exposure on Modified Release and Regular Tacrolimus

2013· article· en· W2333368946 on OpenAlexaff
Guido Filler, Alexander A. Vinks, Shih‐Han S. Huang, Anthony M. Jevnikar, Norman Muirhead

Bibliographic record

VenueTherapeutic Drug Monitoring · 2013
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsWestern University
Fundersnot available
KeywordsTacrolimusMycophenolic acidPharmacokineticsMedicineConcomitantCrossover studyUrologyMycophenolateImmunosuppressionArea under the curveRandomizationPharmacologyTransplantationInternal medicineRandomized controlled trial

Abstract

fetched live from OpenAlex

Concomitant immunosuppression may affect the mycophenolate mofetil exposure. Astellas developed a once-daily modified release formulation of tacrolimus (TacMR) with the potential to reduce the likelihood of nonadherence. It is unknown whether mycophenolic acid (MPA) area under the concentration-time curve (AUC) differs between the 2 tacrolimus (Tac) formulations. In a 2-by-2 crossover design, 20 stable renal transplant recipients on twice-daily Tac either continued their usual Tac therapy (n = 10, group 1) or switched to TacMR for a 12-week period (n = 10, group 2), after which the patients crossed over to the other formulation for another 12-week period. Pharmacokinetic profiles using limited sampling strategies were obtained before randomization (visit 1), and at 12 (visit 2) and 24 weeks (visit 3) at steady state. MPA AUC was calculated using the Pawinski formula. When analyzing visits on Tac, TacMR, and back on Tac combined, the MPA AUC for all 20 patients at baseline was 42.24 (16.98), 37.18 (13.75), and 40.09 (16.69) mg·h·L(-1), respectively, which was not statistically significant using repeated measures (P = 0.1327, R(2) = 0.1109). We conclude that MPA pharmacokinetic profiles are not altered when converting patients from Tac to TacMR.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.244
Threshold uncertainty score0.531

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.028
GPT teacher head0.285
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2013
Admission routes1
Has abstractyes

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