Posttransplant Outcome of Lean Compared With Obese Nonalcoholic Steatohepatitis in the United States: The Obesity Paradox
Bibliographic record
Abstract
Morbid obesity is considered a relative contraindication for liver transplantation (LT). We investigated if body mass index (BMI; lean versus obese) is a risk factor for post-LT graft and overall survival in nonalcoholic steatohepatitis (NASH) and non-NASH patients. Using the United Network for Organ Sharing (UNOS) database, LT recipients from January 2002 to June 2013 (age ≥18 years) with follow-up until 2017 were included. The association of BMI categories calculated at LT with graft and overall survival after LT were examined. After adjusting for confounders, all obesity cohorts (overweight and class 1, class 2, and class 3 obesity) among LT recipients for NASH had significantly reduced risk of graft and patient loss at 10 years of follow-up compared with the lean BMI cohort. In contrast, the non-NASH group of LT recipients had no increased risk for graft and patient loss for overweight, class 1, and class 2 obesity groups but had significantly increased risk for graft (P < 0.001) and patient loss (P = 0.005) in the class 3 obesity group. In this retrospective analysis of the UNOS database, adult recipients selected for first LT and NASH patients with the lowest BMI have the worse longterm graft and patient survival as opposed to non-NASH patients where the survival was worse with higher BMI.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".