Mycophenolate Mofetil Dose Reduction and the Risk of Acute Rejection after Renal Transplantation
Bibliographic record
Abstract
Mycophenolate mofetil (MMF) significantly decreases acute rejection rates after renal transplantation, but intolerance often occurs, leading to dose reduction. The clinical effect of MMF dose reduction has not been clearly established. This study determined whether MMF dose reduction after renal transplantation was associated with subsequent risk of acute rejection. This retrospective cohort study assessed 213 renal transplant recipients. Cox regression was used to model MMF dose as a time-dependent variable, with time to first acute rejection as the primary outcome. One hundred twenty-six patients (59%) had a total of 176 MMF dose reductions during the study. MMF dose was reduced because of leukopenia (55.1%), gastrointestinal symptoms (22.2%), infection (7.4%), malignancy (1.1%), and unknown reasons (14.2%). The cumulative number of days with the MMF dose reduced below full dose was an independent predictor of acute rejection. The relative risk of rejection increased by 4% for every week that the MMF dose was reduced below full dose. No significant association was observed between the number of days with MMF dropped below full dose and allograft failure. The cumulative number of days with the MMF dose dropped below full dose is a significant predictor of acute rejection after renal transplantation. Clinicians need to be aware of the rejection risk when the MMF dose is reduced and maintain close surveillance on such patients.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".