Ethnic Background Is a Potential Barrier to Living Donor Kidney Transplantation in Canada: A Single-Center Retrospective Cohort Study
Bibliographic record
Abstract
BackgroundWe examined if African or Asian ethnicity was associated with lower access to kidney transplantation (KT) in a Canadian setting.MethodsPatients referred for KT to the Toronto General Hospital from January 1, 2003, to December 31, 2012, who completed social work assessment, were included (n = 1769). The association between ethnicity and the time from referral to completion of KT evaluation or receipt of a KT were examined using Cox proportional hazards models.ResultsAbout 54% of the sample was white, 13% African, 11% East Asian, and 11% South Asian; 7% had "other" (n = 121) ethnic background. African Canadians (hazard ratio [HR], 0.75; 95% CI: 0.62-0.92]) and patients with "other" ethnicity (HR, 0.71; 95% CI, 0.55-0.92) were less likely to complete the KT evaluation compared with white Canadians, and this association remained statistically significant in multivariable adjusted models. Access to KT was significantly reduced for all ethnic groups assessed compared with white Canadians, and this was primarily driven by differences in access to living donor KT. The adjusted HRs for living donor KT were 0.35 (95% CI, 0.24-0.51), 0.27 (95% CI, 0.17-0.41), 0.43 (95% CI, 0.30-0.61), and 0.34 (95% CI, 0.20-0.56) for African, East or South Asian Canadians and for patients with "other" ethnic background, respectively.ConclusionsSimilar to other jurisdictions, nonwhite patients face barriers to accessing KT in Canada. This inequity is very substantial for living donor KT. Further research is needed to identify if these inequities are due to potentially modifiable barriers.
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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 | 0.002 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".