Sensory-motor training versus resistance training in the treatment of knee osteoarthritis: A randomized controlled trial
Bibliographic record
Abstract
Objective To compare the effectiveness of sensory-motor training and resistance training in patients with knee osteoarthritis. Design Randomized controlled trial. Setting Istanbul University, Department of Physiotherapy and Rehabilitation. Subjects Forty-eight participants with knee osteoarthritis. Interventions Following baseline assessment, participants were randomly allocated to sensory-motor training (n = 24) and resistance training (n = 24). Both groups received training three times a week for 8 weeks. Main measures The primary outcome measure was the Western Ontario and McMaster Universities Arthritis Index (WOMAC). The secondary outcome measures were pain level, muscle strength, proprioception, range of motion, quality of life, and patient satisfaction with treatment. Patients were assessed before and after four- and eight-week interventions. Results There was no significant difference between the groups’ total WOMAC scores after four- and eight-week interventions (respectively, p = 0.415, p = 0.828). There was a significant improvement in pain level during movement and in the energy subscale SF-36 for resistance training after the four-week intervention (respectively, p = 0.012, p = 0.007). After the eight-week intervention, a significant difference was noted in favor of resistance training in the secondary outcome measure quality of life (QoL). No significant difference was found in other secondary outcomes. Conclusions At the end of the treatment, it was observed that sensory-motor training had a similar effect in the treatment of knee osteoarthritis symptoms to resistance training. These findings may suggest that sensory-motor training is an effective new method to treat patients with knee 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 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 | 0.003 |
| 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".