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Record W3100892944 · doi:10.1111/ajt.16396

Expanding living donor liver transplantation: Report of first US living donor liver transplant chain

2020· article· en· W3100892944 on OpenAlexaboutno aff
Hillary J. Braun, Ana M. Torres, Finesse Louie, Sandra Weinberg, Sang‐Mo Kang, Nancy L. Ascher, John P. Roberts

Bibliographic record

VenueAmerican Journal of Transplantation · 2020
Typearticle
Languageen
FieldMedicine
TopicOrgan Transplantation Techniques and Outcomes
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of Health
KeywordsMedicineABO incompatibilityLiving donor liver transplantationABO blood group systemTransplantationLiver transplantationUnited Network for Organ SharingSurgeryImmunology

Abstract

fetched live from OpenAlex

Living donor liver transplantation (LDLT) enjoys widespread use in Asia, but remains limited to a handful of centers in North America and comprises only 5% of liver transplants performed in the United States. In contrast, living donor kidney transplantation is used frequently in the United States, and has evolved to commonly include paired exchanges, particularly for ABO-incompatible pairs. Liver paired exchange (LPE) has been utilized in Asia, and was recently reported in Canada; here we report the first LPE performed in the United States, and the first LPE to be performed on consecutive days. The LPE performed at our institution was initiated by a nondirected donor who enabled the exchange for an ABO-incompatible pair, and the final recipient was selected from our deceased donor waitlist. The exchange was performed over the course of 2 consecutive days, and relied on the use and compliance of a bridge donor. Here, we show that LPE is feasible at centers with significant LDLT experience and affords an opportunity to expand LDLT in cases of ABO incompatibility or when nondirected donors arise. To our knowledge, this represents the first exchange of its kind in the United States.

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)0.001
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 score0.117
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.016
GPT teacher head0.262
Teacher spread0.246 · 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

Citations26
Published2020
Admission routes1
Has abstractyes

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