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Record W2320015289 · doi:10.14740/jcs300w

Cardiac Surgery at the Time of Simultaneous Liver-Kidney Transplantation

2016· article· en· W2320015289 on OpenAlexvenueno aff
James M. Tatum, Adrienne Quinn, Yuri Genyk, Linda Sher, Lea Matsuoka, Amy E. Hackman, Sophoclis P. Alexopoulos, Mark L. Barr, Michael E. Bowdish, Mark J. Cunningham

Bibliographic record

VenueJournal of Current Surgery · 2016
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsnot available
FundersDivision of Cardiothoracic Surgery, University of Colorado School of Medicine, Anschutz Medical Campus
KeywordsMedicineContraindicationSurgeryTransplantationLiver transplantationKidneyKidney transplantationHeart failureCardiologyInternal medicine

Abstract

fetched live from OpenAlex

Cardiac valve disease is often a contraindication to liver or simultaneous liver-kidney transplantation. The risk of heart surgery in these patients is extremely high, yet uncorrected valve disease jeopardizes transplantation outcomes. Two cases of combined aortic valve replacement at the time of simultaneous liver-kidney transplantation, with 2-month and 3-year postoperative follow-ups, are discussed. Both patients survived surgery and were discharged with good allograft and heart function. At last follow-up, neither experienced graft failure or valve dysfunction, although one patient did develop type 1B rejection of his kidney allograft. In appropriate cases, surgical correction of structural heart disease can be performed at the time of complex abdominal organ transplantation, accomplishing both otherwise contraindicated procedures. J Curr Surg. 2016;6(1):37-40 doi: http://dx.doi.org/10.14740/jcs300w

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.039
GPT teacher head0.311
Teacher spread0.272 · 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 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

Citations6
Published2016
Admission routes1
Has abstractyes

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