Visceral adiposity increases risk for hepatocellular carcinoma in male patients with cirrhosis and recurrence after liver transplant
Bibliographic record
Abstract
Visceral adipose tissue (VAT) is a metabolically active organ, associated with higher risk of malignancies. We evaluated whether VAT is associated with the risk of hepatocellular carcinoma (HCC) in patients presenting with cirrhosis as well as HCC recurrence after liver transplantation (LT). Patients with cirrhosis (n = 678; 457 male) who were assessed for LT (289 with HCC) were evaluated for body composition analysis. Patients who underwent LT (n = 247, 168 male) were subsequently evaluated for body composition, and 96 of these patients (78 male) had HCC. VAT, subcutaneous adipose tissues, and total adipose tissues were quantified by computed tomography at the level of the third lumbar vertebra and reported as indexes (cross‐sectional area normalized for height [square centimeters per square meter]). At the time of LT assessment, the VAT index (VATI) was higher in male patients with HCC compared to non‐HCC patients (75 ± 3 versus 60 ± 3 cm2/m2, P = 0.001). The VATI, subcutaneous adipose tissue index, and total adipose tissue index were higher in male patients with HCC compared to non‐HCC patients. By multivariate analysis, male patients with VATI ≥65 cm2/m2 had a higher risk of HCC (hazard ratio, 1.90; 95% confidence interval, 1.31‐2.76; P = 0.001). In male patients with HCC who underwent LT, a VATI ≥65 cm2/m2 adjusted for Milan criteria was independently associated with higher risk of HCC recurrence (hazard ratio, 5.34; 95% confidence interval, 1.19‐23.97; P = 0.03). Conclusion: High VATI is an independent risk factor for HCC in male patients with cirrhosis and for recurrence of HCC after LT. (Hepatology 2018;67:914–923)
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".