Calcineurin Inhibitor–Free Mycophenolate Mofetil/Sirolimus Maintenance in Liver Transplantation: The Randomized Spare-the-Nephron Trial
Bibliographic record
Abstract
Mycophenolate mofetil (MMF) and sirolimus (SRL) have been used for calcineurin inhibitor (CNI) minimization to reduce nephrotoxicity following liver transplantation. In this prospective, open-label, multicenter study, patients undergoing transplantation from July 2005 to June 2007 who were maintained on MMF/CNI were randomized 4 to 12 weeks after transplantation to receive MMF/SRL (n = 148) or continue MMF/CNI (n = 145) and included in the intent-to-treat population. The primary efficacy endpoints were the mean percentage change in the calculated glomerular filtration rate (GFR) and a composite of biopsy-proven acute rejection (BPAR), graft lost, death, and lost to follow-up 12 months after transplantation. Patients were followed for a median of 519 days after randomization. MMF/SRL was associated with a significantly greater renal function improvement from baseline with a mean percentage change in GFR of 19.7 ± 40.6 (versus 1.2 ± 39.9 for MMF/CNI, P = 0.0012). The composite endpoint demonstrated the noninferiority of MMF/SRL versus MMF/CNI (16.4% versus 15.4%, 90% confidence interval = -7.1% to 9.0%). The incidence of BPAR was significantly greater with MMF/SRL (12.2%) versus MMF/CNI (4.1%, P = 0.02). Graft loss (including death) occurred in 3.4% of the MMF/SRL-treated patients and in 8.3% of the MMF/CNI-treated patients (P = 0.04). Malignancy-related deaths were less frequent with MMF/SRL. Adverse events caused withdrawal for 34.2% of the MMF/SRL-treated patients and for 24.1% of the MMF/CNI-treated patients (P = 0.06). The use of MMF/SRL is an option for liver transplant recipients who can benefit from improved renal function but is associated with an increased risk of rejection (but not graft loss).
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".