Development of physical activity recommendations for adults living with lower limb amputation
Bibliographic record
Abstract
PURPOSE: To develop evidence-based physical activity recommendations for people living with lower-limb amputation (LLA). METHODS: The Appraisal of Guideline, Research and Evaluation protocol (AGREE) II tool was used. A panel of clinicians and researchers with expertise in LLA and guideline development, people with LLA, and a nonprofit advocacy organization for people with LLA was formed. The expert panel then met to refine the scope of the guidelines, review the evidence (based on a systematic review), and formulate the guidelines. Feedback was obtained from partners. RESULTS: For benefits in balance and mobility outcomes, adults with a unilateral major LLA of any etiology, living in the community and using a prosthesis, should perform at least 60 min per week of moderate to vigorous aerobic exercise. This aerobic exercise prescription should be combined with strengthening or balance exercises. Strengthening exercises should include at least 3 sets of 10 repetitions of strengthening exercises for the major muscle groups of the lower limbs at least 2 times per week. Balance exercises should include at least 20 min of balance exercises 3 times per week. There was insufficient evidence to make recommendations for other fitness-related outcomes. CONCLUSION: The AGREE II process led to the development of the first physical activity recommendations for people living with LLA.
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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 | 0.072 | 0.197 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".