Association Between Running Biomechanics And Femoral Cartilage Characteristics In Competitive And Recreational Runners
Bibliographic record
Abstract
Mechanical loading is necessary for articular cartilage maintenance, and recreational runners are at lower risk for knee osteoarthritis (OA). However, the association between mechanical loading and articular cartilage may vary in different types of runners. PURPOSE: To (1) compare femoral cartilage between recreational runners, competitive runners, and controls who do not run and (2) evaluate the association between running biomechanics and femoral cartilage characteristics in each group. METHODS: Ninety individuals (30 per group) were matched on sex, age (± 3 years), and body mass index (±2 kg/m2). Ultrasound imaging was used to measure cartilage thickness, cross-sectional area, and echo-intensity of the medial and lateral regions of the distal femur. Three-dimensional motion capture was used to obtain overground running biomechanics at a preferred speed in standardized footwear. Biomechanical outcomes included the peak external knee flexion (KFM) and adduction moments (KAM), which were normalized to a product of height and weight. Cartilage outcomes were compared between groups using one-way MANOVA. Separate stepwise linear regression models assessed the association between running biomechanics and cartilage outcomes (ΔR2) after accounting for sex and self-reported running amount (km). RESULTS: No differences were found between groups in femoral cartilage outcomes (Pillai’s Trace = 0.227, p = 0.06). Among recreational runners, a larger KFM was associated with a lower medial femoral cartilage echo-intensity (ΔR2 = 0.17, β = -74.42, p = 0.02). No relationships were found between running biomechanics and cartilage outcomes in competitive runners or controls. Among competitive runners, running amount was a significant co-variate, and a greater running amount was associated with higher medial (β = 0.34, p = 0.03) and higher lateral (β = 0.34, p = 0.04) femoral cartilage echo-intensity. CONCLUSIONS: Cartilage echo-intensity increases with OA progression and may provide an indication of cartilage quality. Collectively, findings suggest that greater per-step loading may be associated with greater cartilage quality in recreational runners, but this relationship is lost in competitive runners. Conversely, a high running amount in competitive runners may contribute to lower cartilage quality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.002 | 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".