Anonymous living donation expands access and enhances equity in pediatric liver transplantation: A retrospective cohort study
Bibliographic record
Abstract
Living donor liver transplantation (LDLT) confers the best survival to children with end-stage liver disease, yet racial and socioeconomic barriers often preclude access to a biologically or emotionally related donor. Anonymous nondirected LDLT (A-LDLT), whereby altruistic strangers donate, could close this gap and diminish reliance on deceased-donor LT (DDLT), but its equity and efficacy have not been fully quantified. We therefore analyzed all 422 consecutive pediatric liver transplants at a large Canadian center from January 2005 to March 2023. In this retrospective cohort study, we compared recipient demographics, clinical characteristics, waitlist duration, and survival outcomes across A-LDLT (n=62), directed living donor liver transplantation (n=174), and DDLT (n=186) groups. Children who underwent A-LDLT were disproportionately Black or Indigenous, more often lived in single-parent households, and more frequently spoke a non-English primary language, indicating that anonymous donation reached sociodemographically disadvantaged groups. After adjusting for age, diagnosis, era, and pediatric end-stage liver disease/MELD score, median wait time for cholestatic disease was 104 days with A-LDLT versus 138 days with DDLT-a 20% reduction-while operative complexity, vascular or biliary complication rates, and intensive-care stay were comparable to directed LDLT. One-, 5-, and 10-year patient survival rates after A-LDLT were 100%, 98% and 98%, respectively, mirroring directed living donor liver transplantation and exceeding DDLT (96%, 94%, and 93%). Graft survival showed the same pattern. Integrating anonymous nondirected donors enlarges the living donor pool, decreases time to transplantation for vulnerable children, and preserves the superior long-term outcomes achieved with living donor organs. Embedding A-LDLT alongside DDLT can reduce disparities and enable timely, life-saving transplantation for children without directed donors while maintaining the advantages associated with living donor grafts.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".