The relationship between maximal hip abductor strength and resultant loading at the knee during walking
Bibliographic record
Abstract
The peak external knee adduction moment (KAM) is implicated in progression of knee osteoarthritis (OA). Recently, hip abductor weakness has also been found in patients with knee OA; however, it remains unknown as to how or if this weakness is a consequence of OA, or a predisposing factor. If it is the latter, a direct relationship between hip strength and KAM magnitude would be expected. The purpose of this study was to evaluate the relationship between hip abductor strength and KAM magnitude during walking. In fourteen adults, maximal isometric hip abductor strength was measured, and the KAM was quantified during gait. Additionally, internal hip abductor moments, vertical and medial ground-reaction-forces (GRFs), and GRF to knee joint center lever-arms were quantified during gait. The relationship between hip strength and GRFs, lever-arms and KAM were assessed using correlation. Internal hip abductor moments were compared to maximum hip strength by paired samples t-test. Correlations between hip strength and the vertical GRF (r = -0.05, p = 0.87), medial GRF (r = -0.24, p = 0.41), lever arm (r = -0.01, p = 0.97), and KAM (r = -0.24, p = 0.41) were not statistically significant. Peak internal hip abductor moments during gait (1.1 ± 0.2 Nm/kg) were significantly lower than maximal hip abductor strength (1.8 ± 0.3 Nm/kg, p < 0.001). It is concluded that hip abductor strength is not related to KAM magnitude. It seems more likely that hip abductor weakness is a consequence of OA rather than a predisposing factor.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".