A Study on The Effectiveness of Body Weight Supported Treadmill Training along with Conventional Physiotherapy for Osteoarthritis in Improving Knee Joint Function.
Bibliographic record
Abstract
Background: Osteoarthritis is one of the most prevalent and chronic disabling joint disease of knee joint. It may due to aging, obesity, sedentary lifestyle, overuse, malalignment, and abnormal loading of the joint causes pain and difficulty in walking. Hence, there is a need to study Body Weight Supported Treadmill Training along with conventional physiotherapy for osteoarthritis to restore normal gait patterns by increasing the joint space.Method: This study was a quasi-experimental study of pre and post type carried out in Adhiparasakthi Medical sciences and Research Institute. Melmaruvathur. 60 subjects with knee osteoarthritis were chosen for the study of age above 45 years, accordingto inclusion criteria. They were equally divided into two groups. Group 1, 30 subjects were given with Body weight supported treadmill training with conventional physiotherapy. Group 2 , 30 subjects were given with conventional physiotherapyalone. Treatments were given for 6 sessions for 2 weeks .Both the groups were measured with pre and post-test for pain, range of motion, and walking speed using a Numerical pain rating scale, goniometer, and pedometer respectively.Result: At the end of the treatment program, there is a significant relief of pain, increased knee joint range of motion, and walking speed in patients treated with Body weight-supported treadmill training along with conventional physiotherapy.Conclusion: From this study, it was concluded that the Body weight supported treadmill training along with conventional physiotherapy reduces pain, and increases knee joint range of motion and walking speed among 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".