Steroid Avoidance With Low-Dose Tacrolimus is Safe and Effective in the Long-Term for Kidney Transplant Recipients
Bibliographic record
Abstract
Introduction: In our previous multicenter, open-label, randomized controlled trial (RCT), the SAILOR study, we reported good feasibility, safety, and efficacy of steroid avoidance (SA) at 2 years in immunologically low-risk kidney transplant recipients. A total of 222 participants were randomized to either antithymocyte globulin (ATG) induction + low-dose tacrolimus + mycophenolate mofetil (MMF) or basiliximab induction + low-dose tacrolimus + MMF + prednisolone. Long-term results are needed to confirm the extended safety and efficacy of the SA protocol beyond the short- to medium-term follow-up seen in current reports using low-dose tacrolimus. Methods: In the SAILOR follow-up observational study, we collected clinical data of 215 participants of the original SAILOR trial at 1, 2, 5 years, and at the last follow-up. Results: = 0.27) were similar in the 2 arms. Cumulative incidence of posttransplantation diabetes mellitus in per-protocol population was significantly lower in the steroid-avoidance arm. Serious infections requiring hospitalization, and malignancies did not differ significantly. Two-thirds of participants in the SA arm remained on the steroid-free protocol at the end of follow-up. Conclusion: SA proved to be safe and effective in patients with low immunological risk for up to 7 years following kidney transplantation. Our findings provide robust evidence supporting SA strategy with low-dose tacrolimus without compromising outcomes even at the extended 7-years follow up.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".