Extended experience with a steroid minimization immunosuppression protocol in pediatric renal transplant recipients
Bibliographic record
Abstract
PURPOSE: To determine the safety and efficacy of a novel steroid minimization protocol after renal transplantation at a single Northern California center. INTRODUCTION: We have previously reported our experience on the short-term outcomes in eight children using our steroid minimization protocol. Herein, we present our ongoing experience in using this regimen in 20 children. METHODS: Children receiving immunosuppression with a steroid minimization protocol at our center from 1/04-12/08 (Group 2) were retrospectively compared with 20 controls (Group 1). RESULTS: At one-month follow-up, Group 2 was observed to have lower eGFR, hemoglobin, white cell count, and cholesterol. The incidence of adverse events during the first yr was comparable. Three patients in Group 1 displayed histological evidence of acute rejection, one patient in Group 2 developed humoral rejection; another patient in Group 2 had sub-clinical rejection. Surgical complications were observed in 20% of patients in both groups. While 10% of patients in Group 1 developed diabetes mellitus, none was observed in Group 2. Thirty and 40% of patients in Groups 1 and 2, respectively, suffered from infectious complications during the first yr. CONCLUSIONS: Our novel steroid minimization immunosuppression is safe in children and associated with no increased risk of rejection and infection.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".