De Novo Kidney Transplantation Without Use of Calcineurin Inhibitors Preserves Renal Structure and Function at Two Years
Bibliographic record
Abstract
We performed a randomized prospective trial comparing calcineurin inhibitor (CNI)-free to CNI-based immunosuppression to determine the impact on renal function, structure and gene expression. Sixty-one kidney recipients treated with basiliximab mycophenolate mofetil (MMF) and prednisone (P) were randomly assigned to concentration-controlled sirolimus or cyclosporine. Two years post-transplant 55 patients underwent renal function studies, 48 (87%) underwent transplant biopsies; all classified by Banff scoring and 41 by DNA microarrays. Comparing sirolimus/MMF/P to cyclosporine/MMF/P there was a significantly lower serum creatinine (1.35 vs. 1.81 mg/dL; p = 0.008), higher Cockroft-Gault glomerular filtration rate (GFR) (80.4 vs. 63.4 mL/min; p = 0.008), iothalamate GFR (60.6 vs. 49.2 mL/min; p = 0.018) and Banff 0 (normal) biopsies (66.6 vs. 20.8%; p = 0.013). Regression analysis of calculated GFRs from 1 to 36 months yielded a positive slope for sirolimus of 3.36 mL/min/year, and a negative slope for cyclosporine of -1.58 mL/min/year (p = 0.008). Gene expression profiles from kidneys with higher Banff chronic allograft nephropathy (CAN) scores confirmed significant up-regulation of genes responsible for immune/inflammation and fibrosis/tissue remodeling. At 2 years the sirolimus-treated recipients have better renal function, a diminished prevalence of CAN and down-regulated expression of genes responsible for progression of CAN. All may provide for an alternative natural history with improved graft survival.
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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 | 0.002 |
| 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 | 0.001 |
| 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".