Impact of Skeletal Muscle Mass Index, Intramuscular Adipose Tissue Content, and Visceral to Subcutaneous Adipose Tissue Area Ratio on Early Mortality of Living Donor Liver Transplantation
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Skeletal muscle depletion has been shown to be an independent risk factor for poor survival in various diseases. However, in surgery, the significance of other body components including visceral and subcutaneous adipose tissue remains unclear. METHODS: This retrospective study included 250 adult patients undergoing living donor liver transplantation (LDLT) between January 2008 and April 2015. Using preoperative plain computed tomography imaging at the third lumbar vertebra level, skeletal muscle mass, muscle quality, and visceral adiposity were evaluated by the skeletal muscle mass index (SMI), intramuscular adipose tissue content (IMAC), and visceral to subcutaneous adipose tissue area ratio (VSR), respectively. The cutoff values of these parameters were determined for men and women separately using the data of 657 healthy donors for LDLT between 2005 and 2016. Impact of these parameters on outcomes after LDLT was analyzed. RESULTS: VSR was significantly correlated with patient age (P = 0.041), neutrophil-lymphocyte ratio (P < 0.001), body mass index (P < 0.001), and SMI (P = 0.001). The overall survival probability was significantly lower in patients with low SMI (P < 0.001), high IMAC (P < 0.001), and high VSR (P < 0.001) than in each respective normal group. On multivariate analysis, low SMI (hazard ratio [HR], 2.367, P = 0.002), high IMAC (HR, 2.096, P = 0.004), and high VSR (HR, 2.213, P = 0.003) were identified as independent risk factors for death after LDLT. CONCLUSIONS: Preoperative visceral adiposity, as well as low muscularity, was closely involved with posttransplant mortality.
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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