Clinically‐accessible and laboratory‐derived predictors of biomechanical response to standalone and supported lateral wedge insoles in people with knee osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Lateral wedge insoles (both standalone and those incorporating individualized arch support) have been frequently studied for the effects on knee joint loading and pain in people with knee osteoarthritis. It has been shown that many people who use these insoles do not obtain the intended biomechanical effect, and thus may not experience a clinical benefit. The ability to identify biomechanical responders to lateral wedge insoles before research or clinical intervention is an important objective for efficient resource use and optimizing patient outcomes. The purpose of our exploratory, hypothesis-generating study was to provide an initial assessment of variables that are associated with the biomechanical response to lateral wedge insoles in people with knee osteoarthritis. METHODS: We collected a number of demographic (age, sex, body mass index, foot posture), clinical (knee pain, foot pain, radiographic disease severity), and walking-related (speed, knee alignment, frontal plane subtalar movement, and foot rotation) outcomes from 53 individuals with painful, radiographically-confirmed knee osteoarthritis. The walking-related outcomes were obtained using equipment both from the research laboratory and the clinical setting. We used logistic regression to generate predictive models to determine candidate variables associated with a reduction in the knee adduction moment during walking - a surrogate for tibiofemoral load distribution, and a known biomechanical risk factor for osteoarthritis progression - with the use of standalone and arch-supported lateral wedge insoles. Three different response thresholds (2%, 6%, and 10% reductions in the knee adduction moment) were used. RESULTS: In general, biomechanical responders were those who walked faster, were female, had less varus alignment, and had less severe radiographic severity. Findings were similar between the standalone and arch-supported lateral wedge insoles, as well as between models using the laboratory-derived or clinically-available measures of walking performance. CONCLUSIONS: Our hypothesis-generating study provides valuable information that will inform future research into the efficient and effective use of lateral wedge insoles in the conservative management of knee osteoarthritis.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".