Basiliximab with delayed introduction of calcineurin inhibitors as a renal‐sparing protocol following liver transplantation in children with renal impairment
Bibliographic record
Abstract
Renal impairment is frequently compromised in patients with end-stage liver disease and is associated with increased long-term mortality post-LT. In contrast to CNI, basiliximab is an immunosuppressive agent with minimal nephrotoxic potential. This study reviews the experience of a single pediatric liver transplant center's renal-sparing approach with the use of basiliximab and MMF to compensate for delayed entry of CNI in children with renal impairment at the time of organ availability. There were no differences in renal function between pediatric patients with and without pre-LT renal impairment within the first year (cGFR: 135 mL/min/1.73 m2 vs. 144 mL/min/1.73 m2 ; p = 0.56) or at 5-8 yr following LT, (129 mL/min/1.73 m2 vs. 130 mL/min/1.73 m2 ; p = 0.97). In addition, there was no difference in ACR rates (50% vs. 43%, p = 0.62) between patients in the basiliximab group and those patients receiving standard CNI and steroid strategies. The utilization of a renal-sparing approach with basiliximab alongside delayed entry and lower early target trough levels of CNI in children with renal impairment at the time of LT is safe and maintains excellent long-term kidney function.
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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 | 0.001 |
| 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".