Influence of stretching and strengthening exercise on functional activity in Genu Osteoarthritis patients
Bibliographic record
Abstract
Abstract Genu osteoarthritis is a chronic degenerative joint disease in the cartilage of knee marked by clinical, histological, and radiological changes. In genu osteoarthritis, patients will experience morning stiffness, pain and joint inflammation, range of motion limitation, decreasing of muscle power, joint instability and functional activity disorders. Stretching and strengthening exercises are two techniques that can be used to increase functional activity for patients with osteoarthritis genu. This study aims to determine the different of functional activity in patient with osteoarthritis genu before and after stretching and strengthening exercise. This study was used quasi experimental research method with one group pretest-posttest time series design. The sampling technique was purposive sampling with the number of samples as many as 25 people who met the inclusion criteria such as aged ≥ 40 years, had a Manual Muscle Test value ≥ 3, had contracture of flexor muscle of knee and followed all of the study procedure. The measuring instruments was Western Ontario and McMaster Universities Osteoarthritis Index to determine the functional activity before and after 3 and 6 times of therapy. The data was analysed by paired T test. The results showed that there were an increasing activity of daily living in patient with osteoarthritis genu after 3 times treatment (p=0,001) and 6 times treatment (p=0,001) stretching and strengthening exercise both in woman and man.
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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 | 0.002 |
| 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) | 0.002 | 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".