Severe muscle depletion in patients on the liver transplant wait list: Its prevalence and independent prognostic value
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
As detected by cross-sectional imaging, severe muscle depletion, which is termed sarcopenia, holds promise for prognostication in patients with cirrhosis. Our aims were to describe the prevalence and predictors of sarcopenia in patients with cirrhosis listed for liver transplantation (LT) and to determine its independent prognostic significance for the prediction of waiting-list mortality. Adults listed for LT who underwent abdominal computed tomography/magnetic resonance imaging within 6 weeks of activation were retrospectively identified. The exclusions were hepatocellular carcinoma, acute liver failure, prior LT, and listing for multivisceral transplantation or living related LT. Sixty percent of the 142 eligible patients were male, the median age was 53 years, and the median Model for End-Stage Liver Disease (MELD) score at listing was 15. Forty-one percent were sarcopenic; sarcopenia was more prevalent in males versus females (54% versus 21%, P < 0.001) and increased with the Child-Pugh class (10% for class A, 34% for class B, and 54% for class C, P = 0.007). Male sex, the dry-weight body mass index (BMI), and Child-Pugh class C cirrhosis (but not the MELD score) were independent predictors of sarcopenia. Sarcopenia was an independent predictor of mortality (hazard ratio = 2.36, 95% confidence interval = 1.23-4.53) after adjustments for age and MELD scores. In conclusion, sarcopenia is associated with increased waiting-list mortality and is poorly predicted by subjective nutritional assessment tools such as BMI and subjective global assessment. If this is validated in larger studies, the objective assessment of sarcopenia holds promise for prognostication in this patient population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.000 |
| 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 it