Immunosuppression without calcineurin inhibition: optimization of renal function in expanded criteria donor renal transplantation
Bibliographic record
Abstract
INTRODUCTION: To assess the efficacy of calcineurin inhibitor (CNI)-free immunosuppression vs. calcineurin-based immunosuppression in patients receiving expanded criteria donor (ECD) kidneys. PATIENT AND METHODS: Thirteen recipients of ECD kidneys were enrolled in this pilot study and treated with induction therapy and maintained on sirolimus, mycophenolate mofetil (MMF) and prednisone. A contemporaneous control group was randomly selected comprised of 13 recipients of ECD kidneys who had been maintained on CNI plus MMF and prednisone. RESULTS: For the study group vs. the control group, two-yr graft survival was 92.3% vs. 84.6% (p = NS), two-yr patient survival was 100% vs. 92.3% (p = NS) and the acute rejection rates were 23% vs. 31% (p = NS), respectively. Renal function was significantly better in the study group compared with control up to the six-month mark, after which, it remained numerically but not statistically significant. Complications were more common in the study group, but serious adverse events requiring discontinuation were rare. CONCLUSION: This pilot study demonstrates that CNI-free regimens can be safely implemented in patients receiving ECD kidneys with excellent two-yr patient and graft survival and good renal allograft function. Longer follow-up in larger randomized controlled trials are necessary to establish these findings.
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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 | 0.001 |
| 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".