364.1: Survival benefit of living donor availability for pediatric liver transplantation in a large North American center: An intention-to-treat analysis.
Bibliographic record
Abstract
Background: Living-donor liver transplantation (LDLT) is increasingly adopted for pediatric LT. However, its specific benefits are underexplored. This study conducts an intention-to-treat analysis from listing time to assess LDLT’s effectiveness in the pediatric population. Methods: Pediatric LT candidates (<18years) listed between 2001-2023 at a single Canadian center were categorized as pLDLT (with an evaluated potential live donor) or pDDLT (without a live donor). Multiorgan transplant and retransplant candidates were excluded. Employing Cox proportional-hazard regression, we evaluated pLDLT’s survival impact through a covariate-adjusted analysis (age, sex, Pediatric End-Stage Liver Disease (PELD) score, etiology, body weight <5kg, listing period). Results: Among 474 candidates, 219 (46%) had potential live donors. The pLDLT group was younger than the pDDLT group (median: 9 (IQR:5-41) vs. 28 (IQR:6-108) months, p<0.001). The most common etiology was biliary atresia (pLDLT:53%, pDDLT:28%), while acute liver failure was more prevalent in the pDDLT group (20% vs. 6%, p<0.001). In the pLDLT group, the waitlist dropout rate was 0.5% (n=1), compared to the pDDLT group with a significantly higher dropout rate of 9% (n=23). The median wait time was shorter for pLDLT than pDDLT (1.9 (IQR:1.2-3.9) vs. 2.6 (IQR:1.0-5.2) months, p=0.04). Superior survival rates in the pLDLT group were observed at 1-, 5-, and 10-years post-listing (98.6%, 96.6%, 96.6% vs. 87.6%, 84.4%, 83.1%, log-rank p<0.001) (Figure1A) with an 72% reduced mortality risk (aHR 0.28, 95% CI 0.12-0.64, p=0.003). The survival benefit persisted in the subgroup analysis for biliary atresia and acute liver failure (Figure1B&C). In the as-treated analysis, 67 pDDLT candidates benefited from anonymous living donation, resulting in 258 (57%) receiving LDLT and 192 (43%) DDLT. LDLT recipients demonstrated superior survival (log-rank p=0.003) (Figure1D) with a 65% mortality risk reduction (aHR 0.35, 95% CI 0.13-0.93, p=0.036). Although the number of patients listed annually increased over the study period, the waiting time for DDLT has shortened, potentially connected to an increase in live donors (Figure2A&B). Conclusion: Having a potential live donor is associated with substantial survival benefit. Pediatric programs offering LDLT can expand the donor pool and decrease the waiting time for DDLT. Given its overall superior outcomes, LDLT may become the preferred standard for pediatric liver transplants. Figure 1: Survival outcomes of intention-to-treat and as-treated analyses.Figure 2: Temporal changes of waitlist outcomes and waiting time.
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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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".