Effect of Land-Based Generic Physical Activity Interventions on Pain, Physical Function, and Physical Performance in Hip and Knee Osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to evaluate the effects of land-based generic physical activity interventions on pain, physical function, and physical performance in individuals with hip/knee osteoarthritis, when compared with a control group that received no intervention, minimal intervention, or usual care. METHODS: A systematic search for randomized controlled trials on 11 electronic databases (from their inception up until April 30, 2016) identified 27 relevant articles. According to the compendium of physical activities, interventions were categorized into: recreational activities (tai chi/Baduajin-6 articles), walking (9 articles), and conditioning exercise (12 articles). RESULTS: Meta-analysis for recreational activity (n = 3) demonstrated significant mean difference (MD) of -9.56 (95% confidence interval [CI], -13.95 to -5.17) for physical function (Western Ontario and McMaster Universities Arthritis Index) at 3 mos from randomization. Pooled estimate for walking intervention was not significant for pain intensity and physical performance but was significant for physical function (n = 2) with a MD of -10.38 (95% CI, -12.27 to -8.48) at 6 mos. Meta-analysis for conditioning exercise was significant for physical function (n = 3) with a MD of -3.74 (95% CI, -5.70 to -1.78) and physical performance (6-minute walk test) with a MD of 42.72 m (95% CI, 27.78, 57.66) at 6 mos. The timed stair-climbing test (n = 2) demonstrated a significant effect at 18 mos with a MD of -0.49 secs (95% CI, -0.75 to -0.23). CONCLUSION: Very limited evidence to support recreational activity and walking intervention was found for knee osteoarthritis, in the short-term on pain and physical function, respectively.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".