Prehabilitation: preoperative rehabilitation interventions for lung cancer – a scoping review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Individuals undergoing lung cancer surgery often face significant postoperative challenges, underscoring the importance of identifying effective preoperative rehabilitation strategies to support recovery. Aim: To identify rehabilitation interventions that can be implemented during the preoperative period for individuals with lung cancer undergoing thoracic surgery. Design: Scoping review guided by the Arksey and O'Malley methodological framework. Methods: The research question guiding this review was "What rehabilitation interventions should be implemented in the preoperative period for individuals with lung cancer undergoing surgery?" A comprehensive search was performed across five databases: MEDLINE, Cochrane Central, CINAHL, ScienceDirect, and PubMed. The review included studies that addressed rehabilitation interventions before thoracic surgery for individuals with lung cancer. Results: A total of 19 articles met the inclusion criteria. The findings indicate that combining aerobic endurance, resistance, and respiratory training with preoperative education improves outcomes. In addition, nutritional counseling and brief relaxation/emotion-regulation strategies appear to be valuable components of multimodal prehabilitation programs, though evidence is limited. Conclusion: Preoperative rehabilitation interventions have the potential to enhance functional reserve, reduce postoperative complications, and accelerate recovery in individuals undergoing lung resection for lung cancer.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it