Force Platform Assessment of Postural Balance in Knee Osteoarthritis - A Systematic Review
Bibliographic record
Abstract
Osteoarthritis (OA) is the most common form of progressive joint disease. It presents with pain, stiffness and swelling which leads to muscle weakness and reduced physical function. The involvement of lower limb joints leads to deterioration of proprioception and predisposes to postural instability. Postural sway assessment is an integral component in the institution of goal-oriented treatment for OA. Postural sway assessment consists of various parameters such as Antero-Posterior amplitude, Medio-Lateral amplitude, total sway area, and Center of Pressure velocity. The study aims to systematically appraise the current evidence of different postural sway parameters from force plates and their association with knee OA. A literature search was conducted through PubMed, Scopus, and Web of Science databases. 115 articles were identified for screening, of which 10 studies met the inclusion criteria. The methodological quality of the study was assessed by two independent reviewers using Newcastle-Ottawa Quality Assessment Scale (NOS). 5 out of 9 studies showed significant Anterior-Posterior deviation, 5 out of 6 studies showed significant Center of pressure deviation and 3 out of 9 studies showed significant Medio- Lateral deviation. This review indicates that patients with knee OA sway more in Anterior-Posterior direction as compared to Medio-Lateral direction and can be considered as a key finding while assessing knee pain.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".