Kidney Function Before Pancreas Transplant Alone Predicts Subsequent Risk of End-Stage Renal Disease
Bibliographic record
Abstract
BACKGROUND: Recipients of a pancreas transplant alone (PTA) have varying levels of kidney function at the time of transplantation, but the role of kidney function in predicting the risk of end-stage renal disease (ESRD) after PTA remains unclear. METHODS: A study was conducted on 1,135 adult recipients of a first PTA from January 1, 1994 to December 31, 2009 in the Scientific Registry of Transplant Recipients. ESRD events were derived from the United States Renal Data System. Cox proportional hazards models were fitted to determine the independent association of the estimated glomerular filtration rate (eGFR) by the Chronic Kidney Disease Epidemiology Collaboration formula before PTA and ESRD. The continuous relation between eGFR and ESRD was modeled using fractional polynomial terms. RESULTS: The cumulative probabilities of ESRD for eGFR ≥ 90, 60 to 89.9, and <60 mL/min/1.73 m(2) at 5 years were 3.5, 12.2, and 26.0%, and at 10 years were 21.8, 29.9, and 52.2%, respectively. Patients with eGFR <60 and 60 to 89.9 mL/min/1.73 m(2) were 7.74 (95% CI: 4.37, 13.74) and 3.25 (95% CI: 1.77, 5.97) times more likely to develop ESRD than patients with eGFR ≥ 90 mL/min/1.73 m(2). The fractional polynomial model showed a log-linear relation between eGFR and the hazard ratio for ESRD. The results were robust to several sensitivity analyses. CONCLUSIONS: Kidney function before PTA is a strong independent predictor of ESRD. These results may inform patient selection and the use of targeted interventions to reduce the risk of progressive kidney impairment in this patient population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 teacher head, 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".