Studying Relationship Between Static and Dynamic Balance Indices and Knee Pain Severity in Patients with Knee Osteoarthritis
Bibliographic record
Abstract
Background and Objectives: One of the predisposing factors for postural sway changes in patients with knee osteoarthritis is the severity of knee pain. Therefore, the purpose of this study was to evaluate the relationship between pain severity and static and dynamic balance indices in patients with knee osteoarthritis.Materials and Methods: 15 patients with knee osteoarthritis were selected through simple non-probability sampling. Static and dynamic balance indices were also measured by Biodex system, the pain severity by the Visual Analogue Scale (VAS) in two pre and post time intervals. The treatment was performed for the balance trainings group for 3 weeks and 5 times per week. Paired statistical t-test and Pearson test were used to analyze the data.Results: The results showed that balance trainings resulted in significant improvement in pain severity and dynamic and static balance indices. There was a significant direct correlation between pain severity and anterior-posterior stability index and medial-lateral stability index on two feet with the closed eyes with exercise, respectively (rho = 0.52, p = 0.04) and (rho = 0.53, p = 0.03). There was also a significant indirect correlation between pain severity and anterior-posterior stability index on the affected leg with the closed eyes (rho = 0.60, p = 0.01).Conclusion: The results of the study confirm the direct and indirect relationship between dynamic balance indices and pain intensity; in the future studies the effect of pain on neuromuscular factors should be considered.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".