[A new non-invasive biomechanical therapy for knee osteoarthritis improves clinical symptoms and gait patterns].
Bibliographic record
Abstract
BACKGROUND: The management of knee osteoarthritis (OA) focuses on reducing the levels of pain and disability. Recently, a novel biomechanical device and treatment methodology (AposTherapy) was shown to reduce the knee adduction moment while simultaneously challenging the neuromuscular control system through perturbation. AIM: The purpose of the study was to investigate the changes in gait patterns and clinical measurements following treatment with a novel biomechanical device on patients with knee OA. METHODS: A total of 745 patients with bilateral knee OA were analyzed. Patients completed a gait test, Western Ontario and McMaster Osteoarthritis Index (WOMAC) questionnaire and SF-36 Health Survey at baseline and after 12 weeks. The biomechanical device was individually calibrated to each patient. Shifting the center of pressure, through changes in the location of the biomechanical elements causes realignment and reduction in the knee adduction moment. Furthermore the configuration of the biomechanical element allows training under controlled perturbation. RESULTS: A significant decrease was found in WOMAC pain (28.6%) and WOMAC function (25.2%) following three months of therapy (p<0.001). A significant increase was found in the patients' physical quality of life (17.8%) and mental quality of life (11.0%) (p<0.001). Gait velocity, cadence step length, stance phase and single limb support phase improved significantly following three months of therapy (7.6%, 4%, 3.7% and 1.6%, respectively). CONCLUSIONS: Our results suggest an overall improvement in the gait patterns, level of pain, function and quality of life of patients with knee OA following three months of AposTherapy.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.005 | 0.001 |
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".