Short and Long-Term Outcomes Following Liver Transplantation: A Systematic Review and Meta-Analysis of Piggyback versus Conventional Approach
Bibliographic record
Abstract
Introduction: In adult liver transplantation (LT), Piggyback (PB-LT) and conventional (CON-LT) methods are the most commonly used approaches. However, the clinical outcomes of the two approaches and their survival rates have yet to be well examined. This study aimed to conduct a quantitative meta-analysis focused on the efficacy and safety of PB-LT and CON-LT procedures. Methods: This systematic review and meta-analysis followed the PRISMA standards. The literature search was conducted on certain databases, including Cochrane Library, PubMed, Scopus, and EMBASE. The Newcastle-Ottawa Quality Assessment Scale and the risk of Cochrane Collaboration of bias tool were used to analyze eligible articles and evaluate their quality. Results: The results showed that eight retrospective cohort studies and three RCTs were included. When PB-LT was used instead of CON-LT, perioperative red blood cells consumption decreased substantially (MD -1.49; 95% CI -2.53 to -0.45; p = 0.005), with significantly short hospital stay (MD -1.67; 95% CI -2.13 to -1.22; p = <0.001) and reduced warm (MD -8.7; 95% CI -14.93 to -2.48; p = 0.006) and cold (MD -48.32; 95% CI -61.03 to -35.61; p = <0.001) ischemia durations. Furthermore, there were no significant differences in primary graft nonfunction, total operation duration, hepatobiliary complication, length of ICU stay, 1-year mortality, and 1-year graft survival using either PB-LT or CON-LT. Conclusions: This study found that PB-LT and CON-LT were viable options for adult LT. The PB-LT approach had different short-term outcomes. However, the two approaches had no significant differences in long-term clinical outcome indicators.
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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 | 0.016 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.039 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".