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Record W2887316385 · doi:10.1016/j.jceh.2018.07.006

Role of Exercise in the Management of Hepatic Encephalopathy: Experience From Animal and Human Studies

2018· review· en· W2887316385 on OpenAlexaff
Luise Aamann, Puneeta Tandon, Chantal Bémeur

Bibliographic record

VenueJournal of Clinical and Experimental Hepatology · 2018
Typereview
Languageen
FieldMedicine
TopicLiver Disease and Transplantation
Canadian institutionsCentre Hospitalier de l’Université de MontréalUniversité de MontréalUniversity of Alberta
Fundersnot available
KeywordsHepatic encephalopathyMedicineSarcopeniaEncephalopathyIntensive care medicineMalnutritionDiseaseInternal medicineGlutaminePathophysiologyCirrhosisLiver diseaseChronic liver diseaseClearanceGastroenterologyBioinformaticsUrologyBiology

Abstract

fetched live from OpenAlex

Sarcopenia and malnutrition are common features in patients with hepatic encephalopathy. Ammonia, a factor implicated in the pathophysiology of hepatic encephalopathy, may be cleared by the muscle via the enzyme glutamine synthetase when the liver function is impaired. Hence, optimizing muscle mass in patients suffering from hepatic encephalopathy is a potential strategy to decrease ammonia levels. Exercise could be an efficient therapeutic approach to optimize muscle mass and therefore potentially reduce the risk of hepatic encephalopathy in patients with chronic liver disease. This review reports the current evidence regarding exercise and hepatic encephalopathy from animal and human studies. After defining concepts such as frailty, sarcopenia, and malnutrition, the present knowledge regarding exercise as potential therapy in cirrhotic patients with or without hepatic encephalopathy is discussed. Recommendations and future aspects are also considered.

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: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.114
GPT teacher head0.473
Teacher spread0.359 · 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 designSystematic review
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

Citations13
Published2018
Admission routes1
Has abstractyes

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