Comparing outcomes of deceased-donor and living-donor liver transplants in patients with PVT
Bibliographic record
Abstract
Portal vein thrombosis (PVT) complicates liver transplantation (LT) by hindering portal flow restoration. Some centers still consider PVT a contraindication for living-donor LT (LDLT) due to technical challenges compared to deceased-donor LT (DDLT). We retrospectively analyzed adults undergoing LT with main PVT between 2006 and 2023, excluding tumor thrombi and re-LT. Using 1:1 propensity score matching, we balanced age, MELD score, Yerdel classification, cavernous transformation, and physiological reconstruction methods. The primary endpoint was the 90-day complication rate; secondary endpoints included patient and graft survival. Of 122 patients, 96 were matched (48 LDLT, 48 DDLT). The median age was 57 years (IQR: 50-63), with a median MELD of 18 (IQR: 12-25). Common underlying liver diseases were hepatitis C (26%) and alcoholic liver disease (20%). In all, 85% had PVT Yerdel grade I/II, 11% grade III, and 3% grade IV, with cavernous transformation present in 17%. Physiological end-to-end portal vein reconstruction was performed in 90% of cases, while 10% received reconstruction with jump grafts. No significant differences were observed between LDLT and DDLT in warm ischemia time (57 vs. 58 min, p =0.3), 90-day major (37.5% vs. 39.6%, p =0.99) or minor complications (47.9% vs. 52.1%, p =0.84), portal vein re-thrombosis (12.5% vs. 10.6%, p =0.99), posttransplant dialysis (4% vs. 8%, p =0.65), or ascites (25% vs. 30%, p =0.77). At 1/3/5 years, patient and graft survival rates were similar between LDLT and DDLT recipients (log-rank p =0.8 and p =0.9, respectively). Cox regression showed posttransplant anticoagulation (with low-molecular-weight heparin, factor Xa inhibitors, and vitamin K antagonist) as protective for graft survival (HR 0.3, p =0.005). LDLT can achieve outcomes comparable to DDLT in patients with PVT. PVT should not be considered a contraindication for LDLT in selected patients at experienced centers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".