Living Donor Kidney Versus Simultaneous Pancreas-Kidney Transplant in Type I Diabetics
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Transplant options for type I diabetics with end-stage renal disease include simultaneous pancreas-kidney (SPKT), living donor kidney (LDKT), and deceased donor kidney transplant (DDKT). It is unclear whether SPKT offers a survival benefit over LDKT in the current era of transplantation. The authors compared outcomes of kidney transplant recipients with type I diabetes using data from the Organ Procurement and Transplant Network/United Network for Organ Sharing. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Adult (age 20 to 59) type I diabetics who received a solitary first-time kidney transplant between 2000 and 2007 were studied. Outcomes included overall kidney graft and patient survival. Multivariate analysis was performed using a stepwise Cox proportional hazards model. RESULTS: Kidney graft survival was better for recipients of LDKT compared with SPKT (P = 0.008), although patient survival was similar (P = 0.346). On multivariate analysis, LDKT was associated with lower adjusted risks over 72 mo follow-up of kidney graft failure (HR 0.71; 95% CI 0.61 to 0.83) and patient death (HR 0.78; 95% CI 0.65 to 0.94) versus SPKT. Compared with DDKT, SPKT had superior unadjusted kidney graft and patient survival, partly due to favorable SPKT donor and recipient factors. CONCLUSIONS: Despite more transplants from older donors and among older recipients, LDKT was associated with superior outcomes compared with SPKT and was coupled with the least wait time and dialysis exposure. LDKT utilization should be considered in all type I diabetics with an available living donor, particularly given the challenges of ongoing organ shortage.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".