Kidney transplant practice patterns and outcome benchmarks over 30 years: The 2018 report of the NAPRTCS
Bibliographic record
Abstract
The NAPRTCS has collected clinical information on children undergoing renal transplantation since 1987 and now includes information on 12 920 renal transplants in 11 870 patients. Since the first data analysis in 1989, NAPRTCS reports have documented marked improvements in patient and allograft outcomes after pediatric renal transplantation in addition to identifying factors associated with both favorable and poor outcomes. The registry has served to document and influence practice patterns, clinical outcomes, and changing trends in renal transplantation and also provides historical perspective. This report highlights current practices in an era of major changes in DD kidney allocation and continuing steroid minimization. This report presents outcomes of the patients in the NAPRTCS transplant registry up to end of 2017. In particular, an increase in the cumulative incidence of late first AR has occurred in the most recent cohort, while all prior cohorts had a lower cumulative incidence of late first AR.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".