European Society of Organ Transplantation (ESOT) Consensus Statement on Prehabilitation for Solid Organ Transplantation Candidates
Bibliographic record
Abstract
There is increasingly growing evidence and awareness that prehabilitation in waitlisted solid organ transplant candidates may benefit clinical transplant outcomes and improve the patient's overall health and quality of life. Lifestyle changes, consisting of physical training, dietary management, and psychosocial interventions, aim to optimize the patient's physical and mental health before undergoing surgery, so as to enhance their ability to overcome procedure-associated stress, reduce complications, and accelerate post-operative recovery. Clinical data are promising but few, and evidence-based recommendations are scarce. To address the need for clinical guidelines, The European Society of Organ Transplantation (ESOT) convened a dedicated Working Group "Prehabilitation in Solid Organ Transplant Candidates," comprising experts in physical exercise, nutrition and psychosocial interventions, to review the literature on prehabilitation in this population, and develop recommendations. These were discussed and voted upon during the Consensus Conference in Prague, 13-15 November 2022. A high degree of consensus existed amongst all stakeholders including transplant recipients and their representatives. Ten recommendations were formulated that are a balanced representation of current published evidence and real-world practice. The findings and recommendations of the Working Group on Prehabilitation for solid organ transplant candidates are presented in this article.
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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 | 0.023 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".