Sarcopenia in cirrhosis: from pathogenesis to interventions
Bibliographic record
Abstract
Sarcopenia (severe muscle depletion) is a prevalent muscle abnormality in patients with cirrhosis that confers poor prognosis both pre- and post-liver transplantation. The pathogenesis of sarcopenia is multifactorial and results from an imbalance between protein synthesis and breakdown. Nutritional, metabolic, and biochemical abnormalities seen in chronic liver disease alter whole body protein homeostasis. Hyperammonemia, increased autophagy, proteasomal activity, lower protein synthesis, and impaired mitochondrial function play an important role in muscle depletion in cirrhosis. Factors including cellular energy status, availability of metabolic substrates (e.g., branched-chain amino acids), alterations in the endocrine system (insulin resistance, circulating levels of insulin, insulin-like growth factor-1, corticosteroids, and testosterone), cytokines, myostatin, and exercise are involved in regulating muscle mass. A favored atrophy of type II fast-twitch glycolytic fibers seems to occur in patients with cirrhosis and sarcopenia. Identification of muscle biological abnormalities and underlying mechanisms is required to plan clinical trials to reverse sarcopenia through modulation of specific mechanisms. Accordingly, a combination of nutritional, physical, and pharmacological interventions might be necessary to reverse sarcopenia in cirrhosis. Moderate exercise should be combined with appropriate energy and protein intake, in accordance with clinical guidelines. Interventions with branched chain amino acids, testosterone, carnitine, or ammonia-lowering therapies should be considered individually. Various factors such as dose, type, duration of supplementations, etiology of cirrhosis, amount of dietary protein intake, and compliance with supplementation and exercise should be the focus of future large randomized controlled trials investigating both prevention and treatment of sarcopenia in this patient population.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".