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Record W2763637453 · doi:10.1002/lt.24955

Current status of liver transplantation for cholangiocarcinoma

2017· review· en· W2763637453 on OpenAlexaff
Nicolás Goldaracena, Andre Gorgen, Gonzalo Sapisochín

Bibliographic record

VenueLiver Transplantation · 2017
Typereview
Languageen
FieldMedicine
TopicCholangiocarcinoma and Gallbladder Cancer Studies
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineLiver transplantationIntrahepatic CholangiocarcinomaHepatocellular carcinomaInternal medicineTransplantationLiver cancerLiver diseaseMilan criteriaGastroenterologyOncology

Abstract

fetched live from OpenAlex

Cholangiocarcinoma (CCA) is the second most common liver cancer, and it is associated with a poor prognosis. CCA can be divided into intrahepatic, hilar, and distal. Despite the subtype, the median survival is 12-24 months without treatment. Liver transplantation (LT) is recognized worldwide as a curative option for hepatocellular carcinoma. On the other hand, the initial results for LT for CCA were very poor mainly due to a lack of adequate patient selection. In the last 2 decades, improvements have been made in the management of unresectable hilar CCA, and the results of LT after neoadjuvant chemoradiation have been shown to be promising. This has prompted a consideration of hilar CCA as an indication for LT in some centers. Furthermore, some recent research has shown promising results after LT for patients with early stages of intrahepatic CCA. A better understanding of the best tools to prognosticate the outcomes of LT for CCA is still needed. Here, we aimed to review the role of LT for the treatment of patients with perihilar and intrahepatic CCA. Also, we will discuss the most recent advances in the field and the future direction of the management of this disease in an era of transplantation oncology. Liver Transplantation 24 294-303 2018 AASLD.

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)0.001
metaresearch head score (Gemma)0.002
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: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.122
GPT teacher head0.380
Teacher spread0.258 · 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
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

Citations98
Published2017
Admission routes1
Has abstractyes

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