The effect of walking on cardiorespiratory fitness in adults with knee osteoarthritis
Bibliographic record
Abstract
Walking programs alone or in combination with behavioral interventions have proven effective at improving quality of life among older adults with osteoarthritis (OA). It is unclear, however, whether the combination of both of these treatments is more effective at improving cardiorespiratory fitness in older adults with knee OA than a walking program alone or than unsupervised self-directed walking. In this study, we assessed cardiorespiratory fitness with 3 programs: a structured supervised community-based aerobic walking program with a behavioral intervention (WB; n = 41); a supervised program of walking only (W; n = 42); and an unsupervised self-directed walking program (n = 32). We measured maximal oxygen uptake (V̇O2peak), exercise test duration, and workload, heart rate, and ventilation at maximum aerobic capacity in older adults with knee OA after 6 months of WB, W, or self-directed walking. Overall, V̇O2peak improved by 4% in female walkers (+0.9 ± 2.5 mL O2·kg(-1)·min(-1); p < 0.001) and 5% in male walkers (+1.3 ± 2.7 mL O2·kg(-1)·min(-1); p < 0.001), and the change in fitness was similar with all 3 walking interventions. In conclusion, low- to moderate-intensity walking may improve and (or) prevent decrements in cardiorespiratory fitness in older adults with OA. This response was comparable in supervised walkers with and without a behavioral intervention and in unsupervised self-directed walkers.
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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 | 0.001 |
| 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) | 0.001 | 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".