Optimal surgical workup to ensure safe recovery of the donor after living liver donation – A systematic review of the literature and expert panel recommendations
Bibliographic record
Abstract
BACKGROUND: The essential premise of living donor liver transplantation is the assurance that the donors will have a complication-free perioperative course and a prompt recovery. Selection of appropriate donors is the first step to support this premise and is based on tests that constitute the donor workup. The exclusion of liver pathologies and assessment of liver anatomy and volume in the donor candidate are the most important elements in the selection of the appropriate candidate. OBJECTIVE: To determine whether there is evidence to define an optimal donor surgical workup that would improve short-term outcomes of the donor after living liver donation. DATA SOURCES: Ovid Medline, Embase, Scopus, Google Scholar, and Cochrane Central. METHODS: Systematic review following PRISMA guidelines and recommendations using the GRADE approach derived from an international expert panel. RESULTS: Although a liver biopsy remains the only method to exactly determine the percentage and type of steatosis and to detect other liver pathologies, its routine use is not supported. Both magnetic resonance imaging (MRI) and computed tomography (CT) appear to be adequate for quantifying liver volume; the preference for one or the other is often based on center expertise. MRI is clearly a better technique to assess biliary anatomy, although aberrant biliary anatomy may not be clearly detected. MRI is also more accurate than CT in determining low grades of steatosis. CT angiography is the imaging test of choice to assess the vascular anatomy. There is no evidence of the need for catheter angiography in the modern evaluation of a living liver donor. CONCLUSIONS: A donor liver biopsy is indicated if abnormalities are present in serological or imaging tests. Both MRI and CT imaging appear to be adequate methodologies. The routine use of catheter angiography is not supported in view of the adequacy of CT angiography in delineating liver vascular anatomy. No imaging modality available to quantify liver volume is superior to another. Biliary anatomy is better defined with MRI, although poor definition can be expected, particularly for abnormal ducts.
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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 | 0.041 | 0.104 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.013 |
| Bibliometrics | 0.014 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".