Home-based rehabilitation program for lung cancer patients
Bibliographic record
Abstract
Patients with lung cancer often experience a reduction in exercise tolerance and muscle weakness. Despite the well-recognized effectiveness of pulmonary rehabilitation, few researches have studied its impact in lung cancer patients, particularly among whose awaiting for a lung resection surgery (LRS). Objectives: To investigate the feasibility of a short home-based rehabilitation program (HBRP) in patients with lung cancer awaiting for a LRS and to determine its effectiveness on exercise tolerance and skeletal muscle strength. Methods: Ten patients with lung cancer awaiting for a LRS were invited to a 4-week HBRP including moderate intensity aerobic activities (walking and cycling) and muscular training performed three times weekly. Prior to and after the 4-week HBRP, cardiopulmonary exercise test, six-minute walking test (6MWT) and muscle strengh were measured. Patients were asked to complete a diary including adverse events and training information. Results: No adverse event was reported during the rehabilitation program and 7 patients completed ≥75% of the HBRP. In the latter, the cycle endurance test duration (277±70 Vs 379±165s,p=0.08) and the 6MWT (597±49 Vs 624±39m, p<0.05) tended to be, or significatively, improved with training. There was a significant improvement in strength of triceps and hamstrings (4±4kg and 10±9kg p<0.05, respectively). Conclusion: In patients with lung cancer awaiting for LRS, home-based rehabilitation was feasible and induced some physiological gains, such as improved exercise tolerance and muscle strength. This may be clinically relevant, because poor exercise capacity is a strong predictor of postoperative complications in this population. Project supported by the Canadian Lung Association.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.004 | 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 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".