Trunk lean gait modification and knee joint load in people with medial knee osteoarthritis: The effect of varying trunk lean angles
Bibliographic record
Abstract
OBJECTIVE: To evaluate whether increased lateral trunk lean toward the symptomatic lower extremity during gait in people with medial knee osteoarthritis (OA) immediately alters symptoms or medial knee load, as measured by the external knee adduction moment (KAM). METHODS: Participants with medial knee OA (n = 22) underwent 3-dimensional gait analysis to measure KAM peaks (early and late stance) and KAM impulse. Following the analysis of natural gait, participants were trained to lean their trunk toward the symptomatic leg during ipsilateral stance over 3 randomly ordered conditions (6°, 9°, and 12° lean). A projection screen displayed real-time trunk angles and target levels. Pain/discomfort in the knees, the hip, and the back were measured across conditions. Load-modifying effects of increasing lean magnitudes were investigated using linear mixed models. Mediating effects of peak lean timing and participant characteristics (pain and malalignment) were evaluated. RESULTS: Increased trunk lean reduced all KAM measures (P < 0.001), with larger lean angles achieving greater reductions. Efficacy of load reduction improved with later peak lean timing for all measures of the KAM. Participant characteristics did not mediate the effect of trunk lean on the KAM, and symptoms did not change across conditions (P > 0.05). CONCLUSION: Increased trunk lean reduced medial knee load in a dose-response manner. Slightly later achievement of peak trunk lean improved the load-modifying effect of this gait strategy. No immediate symptomatic changes were identified. Future research should determine if long-term implementation of this gait strategy is feasible and whether it can modify disease symptoms and OA progression.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".