Weight Gain After Orthotopic Liver Transplantation: Is Nonalcoholic Fatty Liver Disease Cirrhosis a Risk Factor for Greater Weight Gain?
Bibliographic record
Abstract
Posttransplant weight gain is common after orthotopic liver transplantation. We sought to determine the extent of weight gain at 5 years after transplantation in patients with nonalcoholic fatty liver disease (NAFLD) cirrhosis versus patients with other types of cirrhosis (non-NAFLD). We studied 126 liver transplants performed between 2005 and 2007 at Saint Luc Hospital, University of Montreal. Seventeen of the 126 patients (13.5%) had NAFLD cirrhosis. Ascites volume was difficult to assess, so we used the body mass index (BMI) at 3 months as the reference BMI. All patients gained weight after transplantation, but BMI increased significantly more and earlier among the NAFLD patients [4.8 versus 1.5 kg/m(2) at 1 year (P = 0.001), 5.0 versus 2.3 kg/m(2) at 2 years (P = 0.01), and 5.6 versus 2.6 kg/m(2) at 5 years (P = 0.009)] in comparison with non-NAFLD patients in unadjusted analyses. The greatest BMI increase over time was investigated with univariate and multivariate logistic regression analyses. The BMI increase was divided into tertiles for each period of time observed. The greatest BMI increase over time was defined as the top tertile of BMI increase. After adjustments for potential confounders (ie, total cholesterol, diabetes, and length of hospital stay), NAFLD was no longer associated with a risk of a greater BMI increase [odds ratio (OR) = 3.73 at 1 year (P = 0.11), OR = 2.15 at 2 years (P = 0.34), and OR = 2.87 at 5 years (P = 0.30)]. These findings suggest the need for multidisciplinary, early, and close weight monitoring for all patients. All patients could benefit from pretransplant counseling regarding weight gain and its consequences.
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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 | 0.002 |
| 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".