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Record W4364354107 · doi:10.1111/ctr.14968

Advances and innovations in living donor liver transplant techniques, matching and surgical training: Meeting report from the living donor liver transplant consensus conference

2023· article· en· W4364354107 on OpenAlexaff
Mark Sturdevant, Swaytha Ganesh, Benjamin Samstein, Elizabeth C. Verna, Manuel I. Rodríguez-Dávalos, Vineeta Kumar, Marwan Abouljoud, Oya Andacoglu, Medhat Askar, Dieter Broering, Juliet Emamaullee, Jean C. Emond, Christine E. Haugen, Michelle T. Jesse, Mureo Kasahara, AnnMarie Liapakis, Didier A. Mandelbrot, Anjana Pillai, Garrett R. Roll, Nazia Selzner, Sukru Emre

Bibliographic record

VenueClinical Transplantation · 2023
Typearticle
Languageen
FieldMedicine
TopicOrgan Transplantation Techniques and Outcomes
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineLiving donor liver transplantationLiver transplantationConsensus conferenceIntensive care medicineSurgeryGeneral surgeryTransplantationInternal medicine

Abstract

fetched live from OpenAlex

The practice of LDLT currently delivers limited impact in western transplant centers. The American Society of Transplantation organized a virtual consensus conference in October 2021 to identify barriers and gaps to LDLT growth, and to provide evidence-based recommendations to foster safe expansion of LDLT in the United States. This article reports the findings and recommendations regarding innovations and advances in approaches to donor-recipient matching challenges, the technical aspects of the donor and recipient operations, and surgical training. Among these themes, the barriers deemed most influential/detrimental to LDLT expansion in the United States included: (1) prohibitive issues related to donor age, graft size, insufficient donor remnant, and ABO incompatibility; (2) lack of acknowledgment and awareness of the excellent outcomes and benefits of LDLT; (3) ambiguous messaging regarding LDLT to patients and hospital leadership; and (4) a limited number of proficient LDLT surgeons across the United States. Donor-recipient mismatching may be circumvented by way of liver paired exchange. The creation of a national registry to generate granular data on donor-recipient matching will guide the practice of liver paired exchange. The surgical challenges to LDLT are addressed herein and focuses on the development of robust training pathways resulting in proficiency in donor and recipient surgery. Utilizing strong mentorship/collaboration programs with novel training practices under the auspices of established training and certification bodies will add to the breadth and depth of training.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.079
GPT teacher head0.358
Teacher spread0.279 · 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 designObservational
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

Citations13
Published2023
Admission routes1
Has abstractyes

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