Feasibility and efficacy of a 12-week supervised exercise intervention for colorectal cancer survivors
Bibliographic record
Abstract
Exercise training improves health-related physical fitness and patient-reported outcomes in cancer survivors, but few interventions have targeted colorectal cancer (CRC) survivors. This investigation aimed to determine the feasibility and efficacy of a 12-week supervised exercise training program for CRC survivors. Feasibility was assessed by tracking participant recruitment, loss to follow-up, assessment completion rates, participant evaluation, and adherence to the intervention. Efficacy was determined by changes in health-related physical fitness. Over a 1-year period, 72 of 351 (21%) CRC survivors screened were eligible for the study and 29 of the 72 (40%) were enrolled. Two participants were lost to follow-up (7%) and the completion rate for all study assessments was ≥93%. Mean adherence to the exercise intervention was 91% (standard deviation = ±18%), with a median of 98%. Participants rated the intervention positively (all items ≥ 6.6/7) and burden of testing low (all tests ≤ 2.4/7). Compared with baseline, CRC survivors showed improvements in peak oxygen uptake (mean change (MC) = +0.24 L·min(-1), p < 0.001), upper (MC = +7.0 kg, p < 0.001) and lower (MC = +26.5 kg, p < 0.001) body strength, waist circumference (MC = -2.1 cm, p = 0.005), sum of skinfolds (MC = -7.9 mm, p = 0.006), and trunk forward flexion (MC = +2.5 cm, p = 0.019). Exercise training was found to be feasible and improved many aspects of health-related physical fitness in CRC survivors that may be associated with improved quality of life and survival in these individuals.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".