Sarcopenia in Chronic Liver Disease: Impact on Outcomes
Bibliographic record
Abstract
Malnutrition is a common complication in patients with end-stage liver disease (ESLD) awaiting liver transplantation (LT). Malnutrition and sarcopenia overlap in etiology and outcomes, with sarcopenia being defined as reduced skeletal muscle mass and muscle function. The purpose of this review was to identify the prevalence of sarcopenia with and without obesity in adults and children with ESLD and to assess the methodological considerations in sarcopenia diagnosis and the association of sarcopenia with pre- and post-LT outcomes. A total of 38 articles (35 adult and 3 pediatric articles) retrieved from PubMed or Web of Science databases were included. In adults, the prevalence rates of pre-LT sarcopenia, pre-LT sarcopenic obesity (SO), post-LT sarcopenia, and post-LT SO were 14%-78%, 2%-42%, 30%-100%, and 88%, respectively. Only 2 adult studies assessed muscle function in patients diagnosed with sarcopenia. The presence of pre-LT sarcopenia is associated with higher wait-list mortality, greater postoperative mortality, higher infection risk and postoperative complications, longer intensive care unit (ICU) stay, and ventilator dependency. The emerging pediatric data suggest that sarcopenia is prevalent in pre- and post-LT periods. In 1 pediatric study, sarcopenia was associated with poor growth, longer perioperative length of stay (total/ICU) and ventilator dependency, and increased rehospitalization in children after LT. In conclusion, there is a high prevalence of sarcopenia in adults and children with ESLD. Sarcopenia is associated with adverse clinical outcomes. The present review is limited by heterogeneity in the definition of sarcopenia and in the methodological approaches in assessing sarcopenia. Future studies are needed to standardize the sarcopenia diagnosis and muscle function assessment, particularly in the pediatric population, to enable early identification and treatment of sarcopenia in adults and children with ESLD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".