Sarcopenia as a Prognostic Index of Nutritional Status in Concurrent Cirrhosis and Hepatocellular Carcinoma
Bibliographic record
Abstract
BACKGROUND AND AIMS: Abnormal body composition such as severe skeletal muscle depletion or sarcopenia has emerged as an independent predictor of clinical outcomes in a variety of clinical conditions. This study is the first study to report the frequency and prognostic significance of sarcopenia as a marker of nutritional status in patients with hepatocellular carcinoma (HCC). METHODS: We analyzed 116 patients with HCC who were consecutively evaluated for liver transplant. Skeletal muscle cross-sectional area was measured by CT. Sarcopenia was defined using previously established cutpoints. RESULTS: Ninety-eight patients were males (85%), and the mean age was 58±6 years. Sarcopenia was present in 35 patients (30%). By univariate Cox analysis, male sex (HR, 3.84; P=0.02), lumbar skeletal muscle index (HR, 0.97; P=0.04), INR (HR, 8.18; P<0.001), MELD score (HR, 1.19; P<0.001), Child-Pugh (HR, 3.95; P<0.001), serum sodium (HR, 0.84; P<0.001), TNM stage (HR, 2.59; P<0.001), treatment type (HR, 0.53; P<0.001), and sarcopenia (HR, 2.27; P=0.004) were associated with increased risks of mortality. By multivariate Cox regression analysis, only MELD score (HR, 1.08; P=0.04), Child-Pugh (HR, 2.14; P=0.005), sodium (HR, 0.89; P=0.01), TNM stage (HR, 1.92; P<0.001), and sarcopenia (HR, 2.04; P=0.02) were independently associated with mortality. Median survival for sarcopenic patients was 16±6 versus 28±3 months in nonsarcopenic (P=0.003). CONCLUSIONS: Sarcopenia is present in almost one third of patients with HCC, and constitutes a strong and independent risk factor for mortality. Our results highlight the importance of body composition assessment in clinical practice.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".