Reported Isolated Pancreas Rejection Is Associated With Poor Kidney Outcomes in Recipients of a Simultaneous Pancreas Kidney Transplant
Bibliographic record
Abstract
BACKGROUND: We hypothesized that many reported and presumed isolated pancreas acute rejection episodes in simultaneous pancreas kidney patients may in fact be missed concordant kidney acute rejection episodes. METHODS: To test this hypothesis, we undertook an analysis of the Organ Procurement and Transplant Network database from 1995 to 2006 to assess the impact of reported isolated pancreas rejection on kidney allograft outcomes. The primary outcome of interest was kidney graft status beyond the first posttransplant year. RESULTS: For overall graft survival, we found that when pancreas alone rejection was compared with no rejection there was a significant difference between the curves (log-rank P<0.0001). In addition, this endpoint was also significant for death censored graft survival (log-rank P=0.0036). For both overall and death censored graft survival the multivariate analyses demonstrated an increased risk (adjusted hazards ratio: 2.46, 3.22, respectively) for patients reported to have pancreas alone rejection. CONCLUSIONS: These results indicate that patients with isolated pancreas rejection have worse renal allograft survival than patients reported as having no acute rejection and fare at least as poorly as those with reported kidney graft rejection supporting the concept of concordance of acute rejection in the majority of patients.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".