Live Donor Liver Transplantation Provides Similar Outcome Compared to Full Graft Liver Transplantation in Patients With Hepatorenal Syndrome.
Bibliographic record
Abstract
Background: We investigated if LDLT vs. full graft deceased donor liver transplantation (DDLT) offers similar outcome for patents with HRS after liver transplantation. Methods: Outcomes of LDLT and DDLT in patients with chronic liver disease with HRS were compared. A matched pair 3:1 study design was used with presence of HRS, Meld score, and preoperative dialysis as matching criteria. Thirty-one patients with HRS receiving a LDLT and 93 HRS patients receiving a full graft DDLT were identified. Liver injury and graft function were assessed by AST, bilirubin, and INR after transplantation. Long-term graft and patient survival, as well as kidney function were investigated. Risk factors for graft loss were evaluated by univariate analysis. Results: LDLT vs. DDLT of patients with HRS was associated with decreased peak AST levels (332 ± 215 U/L vs. 927 ± 1233U/L; p= 0.0001), and similar 7-day bilirubin (144 ± 135 μmol/L vs. 119 ± 122 μmol/L; p= 0.35), and INR levels (1.93 ± 0.62 vs. 1.78 ± 0.78; p= 0.314) as marker of graft injury and function. DDLT had an increased ICU (2 (1-39) days vs.4 (0-93) days; p= 0.01) and hospital stay (26 (4-313) days vs. 29 (0-126) days; p= 0.04) when compared to the LDLT group. Incidence of overall postoperative complications (19% vs. 26%; p= 0.62) was similar between both groups. Postoperative biliary complications were more common in LDLT vs. DDLT patients (23% vs. 6%; p= 0.01). LDLT vs. DDLT patients with HRS had similar graft survival at 1- (80% vs. 82%), at 3- (69% vs. 76%), and 5-years (65% vs. 76%) (p= 0.63), as well as an identical 1- (82% vs. 83%), 3- (77% vs. 72%), and 5-years (77% vs. 72%) patient survival (p= 0.93). Incidence of renal failure post liver transplantation (9% vs. 5%; p= 0.4%), as well as creatinine values 5-years after liver transplantation (129 ± 46 μmol/L vs. 119 ± 46 μmol/L; p= 0.3) were identical between LDLT and DDLT groups. In univariate analysis the use of cyclosporine vs. tacrolimus (HR: 0.36, CI: 0.18-0.72, p= 0.004) and ICU stay (HR: 1.032, CI: 1.01-1.05, p= 0.002) was associated with graft loss, while the type of liver graft (LDLT vs. DDLT) did not impact on graft survival. Conclusion: LDLT results in identical long-term outcome when compared with DDLT in patients with HRS. Patients on the liver transplant waiting list with HRS should be encouraged to proceed with LDLT.
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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 | 0.000 |
| 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) | 0.002 | 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".