P0228 DONOR CHARACTERISTICS AND EFFECT ON OUTCOME AFTER PEDIATRIC LIVER TRANSPLANTATION IN THE SPLIT REGISTRY
Bibliographic record
Abstract
Introduction: Donor characteristics, including time waiting for a donor may influence outcome after pediatric liver transplantation (LT) Methods: From the Studies of Liver Transplantation (SPLIT)-a consortium of 39 pediatric LT centers in the US and Canada, we describe donor characteristics for 1,378 recipients of first liver only grafts, and examine in univariate and multivariate analyses their effect on patient (pt) and graft survival. Results: 51.8% of pts recieved a cadaveric donor (CD) whole organ, 28.0% a reduced or split graft and 17% a living donor (LD) graft. There is an increase in the use of split grafts from 5.9% before 1998 to 10.6% after 1998, whereas the % of LDs has remained constant. Of pts aged <12 mos, 32.1% received a whole organ vs 49.2% of pts aged 1–4 years and 66.5% aged 5–12 years. 65% of children were tranplanted within 6 mos of listing. The mean time to LT was <3 mos for LDs and reduced CDs compared to 6.1 mos for whole grafts. 30% CD recipients were in the ICU at LT compared to 19.2% LD recipients. 66% of LD pts had a PELD score <10, compared to 51.4% of CD pts. ABO incompatabile grafts were used in 2.4% of pts. Mean cold ischemia time for CD compared to LDs was 8.1 vs 3.1 hrs: mean warm ischemia times were similiar 52.2 and 49. mins respectively. Intraoperative blood use was similiar 69 and 79 mls/kg. Overall Kaplan-Meier estimates of 3 year pt and graft survivals were 84% and 76% respectively. Pt survival was comparable regardless of donor-recipient gender match. In unadjusted univariate analyses whole liver recipients had a significantly better pt and graft survival compared to CD reduced, split or LD recipients (Log rank p<0.0001 for both outcomes). Donor age was significant for graft survival, p <0.02. Relative risks for death or graft loss for ABO identical compared to incompatible pts were significantly reduced (RR=0.32 and 0.37 respectively; p=0.003 and 0.0003). In a multivariate model of baseline factors affecting 6 mo pt and graft loss, intraoperative blood use, warm and cold iscemia, and organ type were significant predictors. Conclusion: Donor characteristics affect time to LT, differ by age of recipients, influence the operative procedure and have a significant impact on pt and graft survival.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".