Relation Between Ankle Joint Dynamics and Patellar Tendinopathy in Elite Volleyball Players
Bibliographic record
Abstract
OBJECTIVE: Ankle joint complex dynamics developed during volleyball spike jumps take-offs and landings were quantified to assess potential relations between these joint dynamics and patellar tendinopathy. DESIGN: Three-dimensional kinematic data provided information about movements of the lower limbs, while the kinetic data permitted analysis of ground reaction forces as players took-off and landed from full-speed spike jumps. SETTING: Simulated volleyball court with net in a biomechanics research laboratory. PARTICIPANTS: 10 members of the Canadian Men's National Volleyball Team. From history and physical examination, 3 of the 10 players had patellar tendon pain associated with activity and were diagnosed with patellar tendinopathy at the time of the study. Investigators were blinded about the injury status of the players. INTERVENTIONS: None. MAIN OUTCOME MEASURES: Three-dimensional kinematics and joint moments of the ankle, knee, and hip joints. RESULTS: Our analysis revealed that maximal external tibial rotation occurred at or near maximal dorsiflexion while maximal internal tibial rotation coincided with maximal plantarflexion. The plantarflexion moment was 3 to 10 times greater than all the other moments measured, with the maximal plantarflexor moment being calculated at 0.4 BWm (360 Nm). In blinded logistic regression analyses, we found one of the dynamics variables (inversion moment during the landing of the spike jump) was a significant predictor of patellar tendinopathy. CONCLUSIONS: Coupling the results of the current analysis of ankle joint complex dynamics with previously reported results of knee joint dynamics related to patellar tendinopathy suggests that a cluster of variables linked to patellar tendinopathy includes: high ankle inversion-eversion moments, high external tibial rotation and plantarflexion moments, large vertical ground reaction forces, and high rate of knee extensor moment development.
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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 | 0.002 |
| 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".