The impact of sarcopenia and frailty on decompensation in compensated cirrhosis: A systematic review
Bibliographic record
Abstract
BACKGROUND: Sarcopenia and frailty have a negative prognostic impact in patients with decompensated cirrhosis; however, the impact of these conditions on the prognosis of compensated cirrhosis is unknown. We performed a systematic review to assess the effect of sarcopenia and frailty on decompensation in patients with compensated cirrhosis. METHODS: We searched PubMed and Embase for English-language studies published up to April 2025. The primary outcome was decompensation and the secondary outcome was mortality. We included studies with available data on patients with compensated cirrhosis. RESULTS: Eight studies reporting data on sarcopenia (n=829 patients) and 4 studies (n=552 patients) assessing frailty were included in this systematic review. The prevalence of sarcopenia varied from 8% to 63%. Computed tomography at the L3 level and liver frailty index were the methods most commonly used to evaluate sarcopenia and frailty, respectively. Sarcopenia in patients compensated at inclusion was associated with an increased risk of decompensation in some studies, but not in all. When selected patients with compensated cirrhosis and no previous decompensation were studied, most studies showed no increased risk for first decompensation within the follow-up (12-61 mo). Two studies out of the 4 reported a higher risk of decompensation and mortality in patients with frailty. CONCLUSIONS: We reported that sarcopenia was prevalent in patients with compensated cirrhosis, but, in most studies, did not lead to an independent, increased risk of first decompensation and death. Well-designed, prospective multicenter studies are essential to assess the association between sarcopenia, frailty, and the risk of first decompensation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".