Higher subcutaneous adipose tissue radiodensity is associated with increased mortality in patients with cirrhosis
Bibliographic record
Abstract
Background & Aims Association between sarcopenia and mortality in cirrhosis is well recognised; however, little is known about the clinical implications of adipose tissue radiodensity, indicative of biological features. This study aimed to determine an association between high subcutaneous adipose tissue (SAT) radiodensity and survival, compare the prevalence of high SAT radiodensity between healthy population and patients with cirrhosis, and identify an association between computed tomography (CT)-measured SAT radiodensity and histological characteristics. Methods Adult patients with cirrhosis (n = 786) and healthy donors (n = 129) with CT images taken as part of the liver transplant (LT) assessment were included. Abdominal SAT biopsies (1–2 g) were harvested from the incision site at the time of LT from 12 patients with cirrhosis. Results The majority of patients were male (67%) with a mean model for end-stage liver disease (MELD) score of 15 ± 8. SAT radiodensity above -83 HU in females (sub-distribution hazard ratio [sHR] 1.84, 95% CI 1.20–2.85, p = 0.006) and higher than -74 HU in males (sHR 1.51, 95% CI 1.05–1.18, p = 0.02) was associated with the highest mortality risk after adjusting for confounders in competing risk analysis. The frequency of high SAT radiodensity was 26% for those with cirrhosis, compared with 2% in healthy donors ( p <0.001). An inverse correlation was found between SAT radiodensity and the mean cross-sectional area of SAT adipocytes ( r = -0.67, p = 0.02). Shrunken, smaller adipocytes with expanded interstitial space were predominant in patients with high SAT radiodensity, whereas larger adipocytes with a thin rim of cytoplasm were observed in patients with low SAT radiodensity (744 ± 400 vs. 1,521 ± 1,035 μm 2 , p <0.001). Conclusion High SAT radiodensity frequently presents and is associated with a higher mortality in cirrhosis. SAT morphological rearrangement in patients with high SAT radiodensity might indicate diminished lipid stores and alterations in tissue characteristics. Lay summary Poor quality of subcutaneous adipose tissue (fat under the skin) is associated with higher mortality in patients with end-stage liver disease. Fat cells are smaller in patients with poor adipose tissue quality.
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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 | 0.000 | 0.001 |
| 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) | 0.003 | 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".