The relationship between knee loading during gait and cartilage thickness in nontraumatic and posttraumatic knee osteoarthritis
Bibliographic record
Abstract
The relationship between knee moments and markers of knee osteoarthritis progression has not been examined in different knee osteoarthritis subtypes. The objective was to examine relationships between external knee moments during gait and tibiofemoral cartilage thickness in patients with nontraumatic and posttraumatic knee osteoarthritis. For this cross-sectional study, participants with knee osteoarthritis were classified into two groups: nontraumatic (n = 22; mean age 60 years) and posttraumatic (n = 19; mean age 56 years, history of anterior cruciate ligament rupture). Gait data were collected with a three-dimensional motion capture system sampled at 100 Hz and force plates sampled at 2000 Hz. External knee moments were calculated using inverse dynamics. Cartilage thickness was determined with magnetic resonance imaging (T1-weighted, 3D sagittal gradient-echo sequence). Linear regression analyses examined relationships between cartilage thickness with knee moments, group, and their interaction. A higher knee adduction moment impulse was negatively associated with medial to lateral cartilage thickness ratio (B = -1.97). This relationship differed between participants in the nontraumatic osteoarthritis group (r = -0.56) and posttraumatic osteoarthritis group (r = -0.30). A higher late stance knee extension moment was associated with greater medial femoral condyle cartilage thickness (B = -0.86) and medial to lateral cartilage thickness (B = -0.73). These relationships also differed between participants in the nontraumatic osteoarthritis group (r = -0.61 and r = -0.51, respectively) and posttraumatic osteoarthritis group (r = 0.10 and r = 0.25, respectively). Clinical Significance: The relationship between knee moments with tibiofemoral cartilage thickness differs between patients with nontraumatic and posttraumatic knee osteoarthritis. The potential influence of mechanical knee loading on articular cartilage may also differ between these subtypes.
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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 | 0.003 |
| 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".