Impact of living donor liver with steatosis and idiopathic portal inflammation on clinical outcomes in pediatric liver transplantation: Beijing experience
Bibliographic record
Abstract
Background: To evaluate the impact of steatosis and/or idiopathic portal inflammation (IPI) in living donor livers on recipients' clinical outcomes. Methods: We assessed 305 qualified donor liver samples from June 2013 to December 2018. Donors and recipients' clinical characteristics, including follow-up data were retrieved. The graft and overall survival with/without steatosis or portal inflammation were compared by Kaplan-Meier analysis. Results: For living donors, the medium age of was 31.2 (28, 35.8) years old; liver histopathology showed macrovesicular steatosis: 0-5% 264/305 (86.6%) and 5-30% 41/305 (13.4%), IPI: no 220/305 (72.1%) and mild 85/305 (27.9%). For recipients, the medium age was 1.0 (0.6, 1.5) years old; the median pediatric-end-stage-liver-disease score was 16 (5.0, 26.0) and medium follow-up time was 32.8 (24.8, 52.0) months. Biliary atresia (69.5%) was the main indication for liver transplantation (LT). Conclusions: The presence of steatosis and portal inflammation of the donor liver did not impact the clinical outcomes including transaminase or bilirubin normalization, short-/long-term complications and recipients' survival. However, recipients with high pediatric-end-stage-liver-disease score (>16) receiving donor liver with portal inflammation, but not steatosis, had trend negative effect on recipients' survival. In conclusion, donor livers with mild steatosis and portal inflammation were qualified for pediatric living donor LT. However, donor liver with mild portal inflammation would better not be allocated to recipients with high pediatric-end-stage-liver-disease score. This study provided new evidence in pediatric living donor liver allocation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".