The Impact of Primary Liver Disease and Social Determinants in a Mixed Donor Liver Transplant Program: A Single‐Center Analysis
Bibliographic record
Abstract
Organ allocation in liver transplantation (LT) remains imperfect. Periodic center reviews ensure programs transparently evaluate the impact of practice on access to transplantation, reflecting, in particular, patient (primary disease, social determinants) and program (deceased versus live donation) factors. Adult Ontario residents waitlisted for first LT at Toronto General Hospital from November 2012 to May 2019 were reviewed. Analyses were performed between distance to transplant center, income, education level, population density and primary liver disease, with LT, deceased donor liver transplant (DDLT), living donor liver transplant (LDLT), and delisting. Of 1735 listed patients, 549 were delisted (32%), while 1071 were transplanted (62%), with 819 DDLT recipients (76%) and 252 LDLT recipients (24%), while 115 (7%) remained actively listed at data census. On univariate analysis, DDLT recipients lived 30% closer (median 39.7 versus 60.6 km; P < 0.001), lived in more populous areas (median 8501.0 versus 6868.5 people in a 1-km radius; P < 0.001), and resided in households that annually earned 10% less (median $92,643.17 versus $102,820.89 Canadian dollars; P < 0.001) compared with LDLT recipients. These findings with population density and income differences between DDLT versus LDLT receival remained significant on multivariate modeling even when accounting for primary liver disease. Primary liver disease was a statistically significant factor on multivariate analyses in LT receival (P = 0.001) as well as DDLT versus LDLT receival (P < 0.001). Of patients listed for end-stage liver disease, more patients with autoimmune cholestatic liver diseases received LDLT (34%-41%) than DDLT (27%-30%); this contrasted with patients with noncholestatic diseases LDLT (8%-19%) versus DDLT (37%-59%) receival (P < 0.001). Review of transplant allocation in a large mixed-donor North American liver transplant program demonstrates how patient social determinants and primary liver disease etiology continue to be significantly associated with ultimate transplantation.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".