Kidney Transplantation Outcomes in Canadian Aboriginals
Bibliographic record
Abstract
Aboriginal populations experience a very high rate of end-stage renal disease (ESRD); however, little is known about the outcomes of transplantation in this population. We performed a retrospective database review to determine the short- and long-term outcomes of kidney transplantation in Aboriginals. Adult Aboriginal (AB) and Caucasian (C) individuals receiving primary kidney transplants between 1969 and 2003 in Manitoba, Canada were examined. A total of 705 recipients were included (126 AB and 579 C). AB recipients were younger, had different etiologies of ESRD, longer cold-ischemic times for deceased donor transplants, and higher peak panel reactive antibody levels. At 1 year post-transplant, there was no difference in serum creatinine, acute rejection or graft survival between AB and C recipients. However, AB recipients experienced greater weight gains early post-transplant and were more likely to develop post-transplant diabetes mellitus. AB recipients exhibited inferior 10-year graft (AB 26% vs. C 47%, p < 0.01) and patient survival (AB 50% vs. 75%, p < 0.01). When graft survival was censored for death with a functioning graft, there was no difference between the two groups. Multivariate analysis revealed AB race to be an independent predictor of premature graft failure and patient death. In conclusion, kidney transplant outcomes have historically been inferior in the Manitoba population of Canadian Aboriginals.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".