Sequential<i>vs</i>simultaneous revascularization in patients undergoing liver transplantation: A meta-analysis
Bibliographic record
Abstract
AIM: We undertook this meta-analysis to investigate the relationship between revascularization and outcomes after liver transplantation. METHODS: A literature search was performed using MeSH and key words. The quality of the included studies was assessed using the Jadad Score and the Newcastle-Ottawa Scale. Heterogeneity was evaluated by the χ(2) and I (2) tests. The risk of publication bias was assessed using a funnel plot and Egger's test, and the risk of bias was assessed using a domain-based assessment tool. A sensitivity analysis was conducted by reanalyzing the data using different statistical approaches. RESULTS: Six studies with a total of 467 patients were included. Ischemic-type biliary lesions were significantly reduced in the simultaneous revascularization group compared with the sequential revascularization group (OR = 4.97, 95%CI: 2.45-10.07; P < 0.00001), and intensive care unit (ICU) days were decreased (MD = 2.00, 95%CI: 0.55-3.45; P = 0.007) in the simultaneous revascularization group. Although warm ischemia time was prolonged in simultaneous revascularization group (MD = -25.84, 95%CI: -29.28-22.40; P < 0.00001), there were no significant differences in other outcomes between sequential and simultaneous revascularization groups. Assessment of the risk of bias showed that the methods of random sequence generation and blinding might have been a source of bias. The sensitivity analysis strengthened the reliability of the results of this meta-analysis. CONCLUSION: The results of this study indicate that simultaneous revascularization in liver transplantation may reduce the incidence of ischemic-type biliary lesions and length of stay of patients in the ICU.
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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 | 0.017 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.072 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 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".