P38 Long Term Outcomes on Malnutrition, Sarcopenia and Physical Frailty After Liver Transplantation: Impact of Hepatic Encephalopathy
Bibliographic record
Abstract
Background: The liver is the second most transplanted organ worldwide. Despite the high survival rate after liver transplant (LT), malnutrition, sarcopenia and frailty are still present 3 months after surgery. These post-LT complications are associated with adverse clinical outcomes and decreased quality of life. However, the presence of these long-term complications remains undocumented. Purpose: The primary objective is to determine the prevalence of malnutrition, sarcopenia, and frailty starting from 1 year after LT. The secondary objectives are to describe muscle function, quality of life and employment status in LT recipients and to compare patients with and without history of hepatic encephalopathy (HE). Methods: Cross-sectional observational study is conducted including 80 patients transplanted between 2019 and 2021 at the CHUM in Montreal, Canada. A single virtual meeting is performed with each patient during which nutritional risk (Canadian Nutrition Screening Tool), sarcopenia (SARC-F questionnaire), frailty (FRAIL questionnaire), muscle function (chair stand test), quality of life (SF-36) and employment status are assessed. Results: Sixty-five patients have completed the study (41 men and 24 women) with a mean age of 58.8 ± 10.1 years. We observed that 12.3% of patients were at risk of malnutrition, 20% at risk of sarcopenia whereas 46.2% and 18.5% were prefrail and frail, respectively. The prevalence of the risk of malnutrition, sarcopenia, and frailty remained unchanged up until 3 years after LT. Muscle function was impaired after LT (15.8 ± 5.5s vs. 12.6s in healthy people). Patients with history of HE has higher risk of sarcopenia and frailty after LT. Regarding quality of life, the score of physical heath (61.3% ± 21.7) was slightly below normal and remain unchanged up until 3 years after LT. Unemployment was noted in 69.2% of patients of which 40% were in early retirement for a liver disease-related cause. Conclusion: Up to 3 years after LT, patients are still at risk of malnutrition, sarcopenia, and frailty. The physical component score of their quality of life score is below the score of the general population. The results of this project may help identify appropriate interventions to help reduce or prevent complications in the long-term post-LT.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".