Impact of living donor liver transplantation on long‐term cardiometabolic and graft outcomes in cirrhosis due to nonalcoholic steatohepatitis
Bibliographic record
Abstract
BACKGROUND AND AIM: Non-alcoholic steatohepatitis (NASH) is a leading indication for liver transplantation (LT). This study aimed to determine whether living donor LT (LDLT) recipients experienced less recurrent NASH, cirrhosis, and cardiometabolic complications compared to deceased donor LT (DDLT). METHOD: Patients with LDLT and DDLT for NASH between February 2002 and May 2018 at University Health Network (UHN) were compared. Cox Proportional Hazard model was used to analyze overall survival (OS), Fine and Gray's Competing Risk models were conducted to analyze cumulative incidence of post LT outcomes. RESULTS: One hundred and ninety-nine DDLTs and 66 LDLTs were performed for NASH cirrhosis. Time and rate of recurrence of NAFLD and NASH were comparable in both groups. Graft cirrhosis was more common in DDLT recipients (n = 14) versus LDLT (n = 0) (p < .0001). Significant fibrosis (Fibrosis ≥ F2) developed in 50 recipients (12 LDLT and 38 DDLT) post LT (DDLT vs. LDLT: HR = 1.00, 95% CI = (.52-1.93), p = .91) and there was no difference in time to significant fibrosis (p = .57). There was no difference in development of post-transplant diabetes, dyslipidemia, metabolic syndrome, cardiovascular disease, and cancers. LDLT group had better renal function at 10 years (MDRD eGFR of 57.0 mL/min vs. 48.5 mL/min, p = .047). Both groups had a comparable OS (HR = 1.83 (95% CI = .92-3.62), p = .08). CONCLUSION: Overall, LDLT recipients had significantly better renal function by virtue of having early transplantation in their disease course. LDLT was also associated with significantly less graft cirrhosis, although OS and cardiometabolic outcomes were comparable between LDLT and DDLT.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".