Establishment of emerging practices and research priorities for telerehabilitation in solid organ transplantation: meeting report and narrative literature review
Bibliographic record
Abstract
Solid organ transplantation (SOT) is a life-saving procedure for those with end-stage organ dysfunction. The main goals of SOT are to improve quality of life and daily function, which are supported by pre- and post-transplant rehabilitation. In-person rehabilitation programs have traditionally been the standard-of-care for delivering rehabilitation for SOT patients. Many programs have adopted a virtual delivery model [telerehabilitation (TR)], an approach that has become increasingly used given restrictions to in-person delivery during the COVID-19 pandemic. Presently, TR programs are being used both clinically and in research with variable practices. A 2-day virtual meeting held in February 2023 brought together over 30 Canadian adult and pediatric researchers, clinicians, and patient and family partners across SOT. The meeting objectives were: (1) To facilitate knowledge exchange and dialogue in TR between patient partners, healthcare professionals, researchers, and key stakeholders, and (2) Identify gaps in clinical practice and research in TR. The discussion focused on delivery methods of TR, digital tools, facilitators and barriers of TR, and the effects of TR on physical and mental health in both adult and pediatric populations. This meeting report incorporates a narrative literature review of SOT and rehabilitation articles in the last 20 years. Future directions in TR are highlighted leading to the development of key research priorities targeted towards improved delivery of TR in SOT patients.
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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 | 0.015 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".