DETECTING DIFFERENCES BETWEEN ASYMPTOMATIC AND OSTEOARTHRITIC GAIT IS INFLUENCED BY CHANGING THE KNEE ADDUCTION MOMENT MODEL
Bibliographic record
Abstract
The knee adduction moment is indicative of the degree of medial compartmental loading at the knee joint and has been related to the presence and progression of knee osteoarthritis (OA). Studies have reported differences between OA and asymptomatic groups when measuring the adduction moment at the knee; however, there have been various biomechanical models used to describe this moment. In addition, non-invasive interventions have been shown to decrease the adduction moment but only at certain portions of the gait cycle. The objective of the study was to determine if changing the biomechanical model would affect the ability to detect differences between OA and asymptomatic gait and whether these differences depended on which portion of the gait cycle was analysed. The gait of forty-four asymptomatic and forty-four moderate OA subjects was measured. The adduction moment was calculated using three different biomechanical models commonly used in the literature: a 2D representation of the lower limb, a 3D coordinate system based in the tibia, and a 3D coordinate system based in both the tibia and femur. The adduction moment waveforms were compared between groups for various portions of the gait cycle for all three models. The choice of biomechanical model changed the overall magnitude and shape of the adduction moment waveform. These changes affected the ability to detect group differences using commonly reported parameters of the adduction moment. However, group separation was achieved (regardless of model) when analyzing the overall magnitude of the adduction moment across stance phase and the mid-stance portion of the gait cycle. These results demonstrate that the OA subjects are not unloading the medial compartment of the knee at full weight acceptance as well as the healthy controls. Furthermore, the OA subjects are experiencing a higher medial compartment load that is being sustained for the duration of the stance phase of the gait cycle. Group differences that are not model dependent may be important in understanding the pathomechanics of OA and evaluating interventions. These findings support the need for a better understanding of the anatomical mechanisms associated with the adduction moment.
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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 | 0.008 |
| 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) | 0.001 | 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".