Prehabilitation in patients awaiting liver transplantation
Bibliographic record
Abstract
BACKGROUND: Frailty, malnutrition and sarcopenia lead to a significant increase in morbidity and mortality before and after liver transplantation (LT). Prehabilitation attempts to optimize physical fitness of individuals before major surgeries. To date, little is known about its impact on patients awaiting LT. AIMS: The aim of our scoping review was to describe whether prehabilitation in patients awaiting LT is feasible and safe, and whether it leads to a change in clinical parameters before or after transplantation. METHODS: We performed a systematic review of the literature from 1946 to November 2023 to identify prospective studies and randomized controlled trials of adult LT candidates who participated in an exercise training program. RESULTS: Out of 3262 citations initially identified, six studies were included. Studies were heterogeneous in design, patient selection, intervention, duration, and outcomes assessed. All studies were self-described as pilot or feasibility studies and had a sample size ranging from 13 to 33. Two studies were randomized controlled trials. Two study restricted to patients with cirrhosis who were eligible for liver transplantation or on the transplant list. Exercise programs lasted between 6 and 12 weeks. In terms of feasibility, proportion of eligible patients that were recruited was between 54 and 100%. Program completion ranged between 38 and 90%. Interventions appeared safe with 9 (9.2%) adverse events noted. In the intervention group, improvements were generally noted in peak oxygen consumption and workload, 6-min walking distance, and muscle strength. One study suggested a decrease in post-transplant hospital length of stay. CONCLUSIONS: Overall, it appears that prehabilitation with exercise training is feasible, and safe in patients awaiting LT. Higher quality and larger studies are needed to confirm its impact on pre- and post-transplantation-related outcomes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".