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Record W2061326386 · doi:10.1111/ctr.12031

Living vs. deceased donor liver transplantation for hepatocellular carcinoma: a systematic review and meta‐analysis

2012· review· en· W2061326386 on OpenAlexaff
Robert C. Grant, Lakhbir Sandhu, Peter R. Dixon, Paul D. Greig, David Grant, Ian D. McGilvray

Bibliographic record

VenueClinical Transplantation · 2012
Typereview
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineHepatocellular carcinomaMeta-analysisHazard ratioLiver transplantationConfidence intervalInternal medicineMilan criteriaLiving donor liver transplantationSystematic reviewTransplantationGastroenterologyOncologySurgeryMEDLINE

Abstract

fetched live from OpenAlex

Experimental studies suggest that the regenerating liver provides a "fertile field" for the growth of hepatocellular carcinoma (HCC). However, clinical studies report conflicting results comparing living donor liver transplantation (LDLT) and deceased donor liver transplantation (DDLT) for HCC. Thus, disease-free survival (DFS) and overall survival (OS) were compared after LDLT and DDLT for HCC in a systematic review and meta-analysis. Twelve studies satisfied eligibility criteria for DFS, including 633 LDLT and 1232 DDLT. Twelve studies satisfied eligibility criteria for OS, including 637 LDLT and 1050 DDLT. Altogether, there were 16 unique studies; 1, 2, and 13 of these were rated as high, medium, and low quality, respectively. Studies were heterogeneous, non-randomized, and mostly retrospective. The combined hazard ratio was 1.59 (95% confidence interval [CI]: 1.02-2.49; I(2) = 50.07%) for DFS after LDLT vs. DDLT for HCC, and 0.97 (95% CI: 0.73-1.27; I(2) = 5.68%) for OS. This analysis provides evidence of lower DFS after LDLT compared with DDLT for HCC. Improved study design and reporting is required in future research to ascribe the observed difference in DFS to study bias or biological risk specifically associated with LDLT.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.876
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0100.006
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.262
GPT teacher head0.382
Teacher spread0.120 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations91
Published2012
Admission routes1
Has abstractyes

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