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Record W2166406102 · doi:10.1002/lt.23978

Severe muscle depletion predicts postoperative length of stay but is not associated with survival after liver transplantation

2014· letter· en· W2166406102 on OpenAlexaffabout
Aldo J. Montaño‐Loza

Bibliographic record

VenueLiver Transplantation · 2014
Typeletter
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsUniversity of Alberta HospitalAlberta Hospital Edmonton
Fundersnot available
KeywordsMedicineSarcopeniaLiver transplantationContraindicationTransplantationLiver diseaseBody mass indexCohortInternal medicineModel for End-Stage Liver DiseaseQuartileSurgeryPathologyConfidence interval

Abstract

fetched live from OpenAlex

We thank Drs. Clark and Cross for their interest in our study1 and will respond to their comments. We agree that one limitation of our study is that only patients who went on to receive liver transplantation were included, and patients who could have had sarcopenia might not have been listed. However, none of our patients evaluated for liver transplantation have been rejected solely on the basis of sarcopenia. The current evidence suggests that only “extreme sarcopenia,” previously defined differently as the lowest tertile of the total psoas area (TPA),2 the lowest quartile of the TPA,3 or the lowest sextile of the third lumbar skeletal muscle index,1 should be considered a contraindication for liver transplantation. On the other hand, in our cohort of patients, all underwent a nutritional evaluation as part of the liver transplant assessment with advice about increasing protein intake and leucine supplementation, but none of them had nasogastric or nasoenteral feeding. We normally used nasogastric or nasoenteral feeding only for those patients with a body mass index less than 18.5 kg/m2 because this has been shown to be a risk factor for mortality after liver transplantation,4 but none of the patients in this cohort had a body mass index below this threshold. Finally, because current methods used to assess liver disease severity, such as the Model for End-Stage Liver Disease (MELD) score, do not give a functional assessment of the patient's fitness, we believe that the next step is to evaluate the development of composite scores, including new scores such as MELD-sarcopenia and MELD-psoas,5, 6 or to assign exemption points to those patients with sarcopenia so that they can undergo transplantation before they develop extreme sarcopenia. Nevertheless, this issue should be evaluated preferentially in prospective and multicenter controlled clinical trials.7 Aldo J. Montano-Loza, M.D., M.Sc., Ph.D. Division of Gastroenterology and Liver Unit University of Alberta Hospital Edmonton, Alberta, Canada

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)0.010
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 score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.260
Teacher spread0.231 · 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

Citations236
Published2014
Admission routes2
Has abstractyes

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