Review article: prognostic significance of body composition abnormalities in patients with cirrhosis
Bibliographic record
Abstract
BACKGROUND: Recent advances in evaluation of body composition show body mass index to be inadequate in differentiating between body compartments in cirrhosis. Given the limitations of body mass index, body composition evaluation using computed tomography has been increasingly used as a non-invasive clinical tool with prognostic value. Another factor influencing prognosis includes sex-specific differences in body composition that are seen in cirrhosis. AIM: To review current knowledge regarding the frequency and clinical implications of abnormal body composition features in cirrhosis. METHODS: We searched PubMed database and limited the literature search to full-text papers published in English. Studies using inappropriate landmarks or demarcation of body composition components on computed tomography images were eliminated. RESULTS: Sarcopenia is a well established factor affecting morbidity and mortality in cirrhosis. Other important body composition components that have been overlooked thus far include subcutaneous adipose tissue and visceral adipose tissue. Female patients with cirrhosis and low subcutaneous adiposity have a higher risk of mortality, whereas male patients with high visceral adiposity have a higher risk of hepatocellular carcinoma and recurrence following liver transplantation. Increased adipose tissue radiodensity has been associated with risk of decompensation and mortality. CONCLUSIONS: Further evaluation of body composition abnormalities may help with development of targeted therapeutic strategies and improve outcome in patients with cirrhosis. Moreover, recognition of these abnormalities could improve prioritisation for liver transplantation as our current method based solely on liver function might lead to risk misclassification.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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".