Biomechanical effects of different knee sleeves on early unilateral knee osteoarthritis in 6 weeks intervention / Nahdatul Aishah Mohd Sharif
Bibliographic record
Abstract
Knee osteoarthritis (OA) is a common joint disorder that affects balance, knee joint proprioception and gait. Many treatment approaches have been used to improve the conditions of people with this disease. Knee sleeves are often prescribed to alleviate pain. However, the biomechanics underlying their pain-relieving effect is still not well understood. This pre-post study is aimed at evaluating and comparing the effects of two different types of knee sleeves on gait biomechanics and postural stability of people with early knee OA, and to determine the relationship of these changes to patient-reported pain outcomes following a six-week application. Patients with clinically diagnosed knee OA were recruited from the University of Malaya Medical Centre (UMMC), and were randomly assigned to two test groups comprising those using: 1) a simple sleeve, and 2) a simple sleeve with patella cutout. The walking motion and the ground reaction forces of participants were measured using Vicon Nexus motion analysis system (with five cameras) and two Kistler force plates, with sampling rates of 100Hz (kinematics) and 1,000Hz (kinetics), respectively for two walking speeds – controlled and self-selected. The postural stability was measured using Biodex Stability System (BSS) – with seven protocols – to obtain the Overall Stability Index (OSI): Postural Stability Test (PST), and Athlete Single Leg Test (ASL) – static and dynamic conditions – and Fall Risk Test (FRT). Pain, stiffness and physical functions were recorded using the Western Ontario and McMaster Universities Arthritis Index (WOMAC). SPSS v22 was used for statistical analyses, with two-way repeated measures Analysis of Variance (ANOVA) with mixed approaches were used to compare knee sleeve designs (between-subject effects) against all dependent variables (within-subject effect), with additional Bonferroni corrections for multiple tests and confidence interval. All measurements were made before, immediately after, and following six weeks of knee sleeve application (primary time point). Seventeen participants (aged 47.7±9.7 years) with early unilateral knee OA completed the study. iii Overall results show significant reduction in pain, early stance and late stance knee adduction moment, and increased walking speed after six weeks of sleeve application. However, there are no significant differences between the groups in all parameters at all points of measurements. The results indicate that there is improvement in overall stability index (OSI) but no significant changes are detected for static and dynamic PST for both types of sleeves immediately after application. For ASL, there is significant reduction in OSI in the affected knee in the static test (p=0.042), and in the unaffected knee in the dynamic test (p=0.034) in both groups. The findings show that early knee OA patients could experience improved balance ability in both static and dynamic conditions, and less pain after six weeks of knee sleeve application. This study results suggest that knee sleeves can reduce knee adduction moments in early unilateral knee OA by 14.0% and 12.1% using the simple sleeve and the sleeve with patella cutout, respectively, and possibly delay disease progression. Additionally, knee sleeve with patella cutout does not provide additional benefits when compared to the simple knee sleeve.
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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 | 0.000 |
| 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".