Towards a common definition of surgical prehabilitation: a scoping review of randomised trials
Bibliographic record
Abstract
BACKGROUND: There is no universally accepted definition for surgical prehabilitation. The objectives of this scoping review were to (1) identify how surgical prehabilitation is defined across randomised controlled trials and (2) propose a common definition. METHODS: The final search was conducted in February 2023 using MEDLINE, Embase, PsycINFO, Web of Science, CINAHL, and Cochrane. We included randomised controlled trials (RCTs) of unimodal or multimodal prehabilitation interventions (nutrition, exercise, and psychological support) lasting at least 7 days in adults undergoing elective surgery. Qualitative data were analysed using summative content analysis. RESULTS: We identified 76 prehabilitation trials of patients undergoing abdominal (n=26, 34%), orthopaedic (n=20, 26%), thoracic (n=14, 18%), cardiac (n=7, 9%), spinal (n=4, 5%), and other (n=5, 7%) surgeries. Surgical prehabilitation was explicitly defined in more than half of these RCTs (n=42, 55%). Our findings consolidated the following definition: 'Prehabilitation is a process from diagnosis to surgery, consisting of one or more preoperative interventions of exercise, nutrition, psychological strategies and respiratory training, that aims to enhance functional capacity and physiological reserve to allow patients to withstand surgical stressors, improve postoperative outcomes, and facilitate recovery.' CONCLUSIONS: A common definition is the first step towards standardisation, which is needed to guide future high-quality research and advance the field of prehabilitation. The proposed definition should be further evaluated by international stakeholders to ensure that it is comprehensive and globally accepted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.077 | 0.196 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.017 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.007 | 0.007 |
| 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".