Self-administered acupressure and exercise for patients with osteoarthritis: A randomized controlled trial
Bibliographic record
Abstract
Objective Knee osteoarthritis is a prevalent degenerative joint disease and seriously affects the athletic abilities of middle-aged and elderly patients. Acupressure is a traditional non-pharmacological intervention that promotes blood circulation and muscle activity. Self-administrated acupressure and exercise can be potential management for knee osteoarthritis. Design It is a randomized and controlled trial for knee osteoarthritis self-treatment. Settings Cangzhou Hospital. Interventions 221 patients with knee osteoarthritis were recruited and randomly divided into 4 groups: control group ( n = 55), exercise group ( n = 56), acupressure group ( n = 55) and exercise & acupressure group ( n = 55). In the first eight weeks, corresponding training courses were provided to different groups of patients. The patients were asked to carry out their own corresponding interventions for 16 weeks. The patient‘s condition was evaluated in the sixteenth week. Main measures The Western Ontario and McMaster Universities global scores of knee osteoarthritis patients were assessed at the 8th and 16th week of our trial. Results Self-administered acupressure and exercise significantly decreased visual analogue scale (3.75 ± 1.89 versus 2.93 ± 1.73, p < 0.05), pain (7.6 ± 2.8 versus 4.8 ± 2.7, p < 0.05), stiffness (3.75 ± 1.89 versus 2.93 ± 1.73, p < 0.05) at the 16th week ( p < 0.05) in patients with knee osteoarthritis compared to other intervention. The combination of acupressure and exercise also improved the range of motion (114.4 ± 11.5 versus 120.4 ± 11.9, p < 0.05) and walk speed (1.48 ± 0.48 versus 1.76 ± 0.50, p < 0.05) of osteoarthritis patients ( p < 0.05). Conclusion Self-administrated exercise and acupressure alleviate the arthritic symptoms (swelling, pain, joint dysfunction and joint deformities) and improve the joint functions, supporting its potential use in the clinical management for osteoarthritis.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".