The prognostic value of sarcopenia in acute-on-chronic liver failure: a systematic review and meta-analysis
Bibliographic record
Abstract
Sarcopenia is prevalent in patients with chronic liver diseases, especially in cirrhosis patients. While sarcopenia is identified as a predictor of mortality in cirrhosis, its influence on acute-on-chronic liver failure (ACLF) remains unclear. This systematic review with meta-analysis aimed to explore the prognostic value of sarcopenia in ACLF patients. A comprehensive online literature search was performed in Medline (via PubMed), Web of Science, Embase, and Cochrane Library, and eligible studies were screened according to the predetermined criteria. The quality of the included studies was assessed by using the revised Cochrane Collaboration Risk of Bias Tool for randomized-control studies and the Newcastle-Ottawa Quality Assessment Scale for observational studies. Available outcomes measured by odds ratio (OR), hazard ratio (HR), and risk ratio (RR) with a 95% confidence interval (CI) were extracted and further included in the meta-analysis. Stata (version 18.0) was used for all statistical analyses. Nine studies were included in further analysis. The pooled prevalence of sarcopenia was 53.3% (95% CI: 53.26 − 71.23%). The presence of sarcopenia was positively associated with 28-day mortality (HR = 2.11, 95% CI: 1.50–2.95, p < 0.001, I 2 = 0.0%; OR = 2.73, 95% CI: 1.37–5.42, p = 0.004, I 2 = 0.0%), 90-day mortality (HR = 1.66, 95% CI: 1.13–2.46, p = 0.01, I 2 = 72.3%), and overall mortality (HR = 1.81, 95% CI: 1.30–2.51, p < 0.01, I 2 = 0.0%). When using continuous variables to describe sarcopenia, a 1-unit increase in these indicators was almost significantly related to reduced 90-day mortality (HR = 0.98, 95% CI: 0.95-1.00, p = 0.052, I 2 = 0.0%) and significantly associated with lower 1-year post-transplantation mortality (HR = 0.91, 95% CI: 0.85–0.98, p = 0.012, I 2 = 32.7%). Current evidence illustrates that sarcopenia is an unfavorable factor for both short- and long-term prognosis. More studies are needed to validate these findings in the future.
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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 | 0.013 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.042 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".