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Record W2373384082

Hepatic vein reconstruction in living donor right fiver transplantation

2006· article· en· W2373384082 on OpenAlexaboutno aff
Yuanting Liu

Bibliographic record

VenueZhonghua putong waike zazhi · 2006
Typearticle
Languageen
FieldMedicine
TopicOrgan Transplantation Techniques and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInferior vena cavaSurgeryVeinTransplantationLiver transplantationLiving donor liver transplantation
DOInot available

Abstract

fetched live from OpenAlex

Objective To-evaluate the effect of hepatic vein reconstruction in living donor right liver transplantation for adult patients. Methods From August 2004 to March 2005,29 adult patients received right liver transplantation without inclusion of middle hepatic vein in the graft in Toronto General Hospital. Right hepatic veins (RHV) were anastomosed to the recipient's RHV end-to-end or end to side to recipient's inferior vena cava(IVC). Inferior right hepatic veins (IRHV) with the diameter≥5mm were anastomosed to recipient's IVC by end-to-side. Major middle hepatic vein (MHV) tributaries (V8 and V5) with a diameter larger than 5mm were preserved and reconstructed by a venous graft. Blood flow was checked by Doppler ultrasound intraoperatively and every day postoperatively. CT was performed in 3 months after transplantation. Results RHV was anastomosed to the recipient's RHV by end-to-end in 17 patients, to recipient's IVC by end-to-side in 12 patients. IRHV was anastomosed to recipient's IVC by end- to-side in 10 patients. MHV tributaries (V8 and V5) were reconstructed in 15 patients. Venous flow and the right liver graft regeneration were satisfactory. Conclusions This venous reconstruction in case of adult living donor right liver transplantation is simple and practical, and the result is satisfactory.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.225
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations0
Published2006
Admission routes1
Has abstractyes

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