Identification of new donor variables associated with graft survival in a single-center liver transplant cohort
Bibliographic record
Abstract
We currently face the more widespread use of marginal livers for organ transplantation. Therefore, it is imperative to adequately identify the factors affecting early and late graft survival in that setting. The objective of this study was to determine the donor variables associated with graft survival in the liver transplant program of the University of Montreal. We retrospectively studied the survival of 634 grafts transplanted into 634 recipients between 1990 and 2008. The variables associated with 1- and 5-year graft survival were identified with the Cox proportional hazards regression model. The donor population was characterized by a mean age of 45.24 ± 18.15 years; 52.8% had at least 1 of the currently recognized extended criteria donor factors. The recipients had a mean age of 52.51 ± 10.80 years and a mean Child-Pugh score of 9.58 ± 2.32. Liver grafts were considered inadequate with respect to their gross appearance in 16 cases (2.5%). The 1- and 5-year graft survival rates were 78.7% and 71.1%, respectively. According to a Cox regression multivariate analysis, the independent determining factors associated with graft survival were (1) the graft appearance (P < 0.001 at 1 and 5 years), (2) the donor partial pressure of oxygen/fraction of inspired oxygen ratio (P = 0.005 at 1 year and P < 0.005 at 5 years), and (3) the donor hemoglobin level (P = 0.008 at 1 year and P = 0.005 at 5 years). In conclusion, the gross graft appearance, the presence of donor lung diffusion abnormalities, and the donor hemoglobin levels were significantly associated with graft survival. These observations, if they are confirmed, could improve our ability to select marginal organs.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".