Effect of Closed Kinetic Chain Exercise to Reduce Pain and Increase Functional Ability in Patient with Osteoarthritis Genu
Bibliographic record
Abstract
Background: Osteoarthritis genu is a degenerative disease with symptoms of chronic inflammation of the joint cartilage which causes pain, limited movement and function. Closed kinetic chain exercise is an active movement that involves many joints and muscle groups simultaneously. This study aims to analyze the effect of closed kinetic chain exercise on reducing pain and increasing functional ability in osteoarthritis genu. Subjects and Method: Quasi experimental research with a research approach in the form of pretest and posttest with control group design. This study was conducted at RST dr. Soedjono Magelang in May-June 2023. A total of 20 osteoarthritis genu patients were divided into two groups: (1) The intervention group was given closed kinetic chain exercise and (2) The control group was given conventional physiotherapy. Pain level was measured using the Visual Analog Scale (VAS). Functional ability was measured by the Western Ontario and McMaster Osteoarthritis Index (WOMAC). Mean differences between the closed kinetic chain exercise group and the conventional physiotherapy group were analyzed using the independent t-test. Results: Providing closed kinetic chain exercise is effective in reducing the level of silent pain (Effect Size = 1.20; p= 0.014), movement pain (Effect Size= 0.99; p= 0.004), movement pain (Effect Size= 1.37; p= 0.023), and increasing functional ability in osteoarthritis genu patients (Effect Size = 0.10; p= 0.023). Conclusion: Providing closed kinetic chain exercise can reduce pain and increase functional ability in osteoarthritis genu. Keywords: Closed Kinetic Chain Exercise; Painful; Functional Capabilities; Osteoarthritis Genu Correspondence: Siti Fadhilah, Bachelor of Physiotherapy, Universitas Muhammadiyah Surakarta, Indonesia. Perumahan Koperasi Putri Tujuh Blok D17 RT 026 Bagan Besar Dumai Riau. Email: j120221270@student.ums.ac.id. Mobile: 081267705503
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.004 | 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".