Factors Influencing Ethnic Disparities in Outcomes after Deceased Donor Kidney Transplantation
Bibliographic record
Abstract
Abstract Background: African American (AA) recipients of deceased-donor (DD) kidney transplants (KT) have shorter allograft survival than recipients of other ethnic groups. Reasons for this disparity encompass complex interactions between donors and recipients characteristics. Methods: Outcomes from 3,872 AA and 19,719 European American (EA) DDs who had one kidney transplanted in an AA recipient and one in an EA recipient were analyzed. Four donor/recipient pair groups (DRP) were studied, AA/AA, AA/EA, EA/AA, and EA/EA. Survival random forests and Cox proportional hazard models were fitted to rank and evaluate modifying effects of DRP on variables associated with allograft survival. These analyses sought to identify factors contributing to the observed disparities in transplant outcomes among AA and EA DDKT recipients. Results: Transplant era, discharge serum creatinine, delayed graft function, and DRP were among the top predictors of allograft survival and mortality among DDKT recipients. Interaction effects between DRP with the kidney donor risk index and transplant era showed significant improvement in allograft survival over time in EA recipients. However, AA recipients appeared to have similar or poorer outcomes for DDKT performed after 2010 versus before 2001; allograft survival hazard ratios (95% CI) were 1.15 (0.74, 1.76) and 1.07 (0.8, 1.45) for AA/AA and EA/AA, compared to 0.62 (0.54, 0.71) and 0.5 (0.41, 0.62) for EA/EA and AA/EA DRP, respectively. Recipient mortality improved over time among all DRP, except unemployed AA/AAs. Relative to DDKT performed pre-2001, employed AA/AAs had HR=0.37 (0.2, 0.69) versus 0.59 (0.31, 1.11) for unemployed AA/AA after 2010. Conclusion: Relative to DDKT performed before 2001, similar or worse overall DCAS was observed among AA/AAs, while EA/EAs experienced considerable improvement regardless of employment status, KDRI, and EPTS. AA recipients of an AA DDKT, especially if unemployed, had worse allograft survival and mortality and did not appear to benefit from advances in care over the past 20 years.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".