Association of Hip and Foot Factors With Patellar Tendinopathy (Jumper's Knee) in Athletes
Bibliographic record
Abstract
Background Investigations on the causes of patellar tendinopathy should consider impairments at the hip and foot/ankle because they are known to influence movement patterns and affect patellar tendon loading. Objectives To investigate hip and foot/ankle impairments associated with patellar tendinopathy in volleyball and basketball athletes using classification and regression tree analysis. Methods In this clinical measurement, cross-sectional study, 192 athletes were assessed for impairments of the hip and foot/ankle, including shank-forefoot alignment, dorsiflexion range of motion (ROM), iliotibial band flexibility, passive hip internal rotation ROM, and hip external rotator and hip abductor isometric strength. Athletes with tenderness and/or pain at the inferior pole of the patella were considered to have patellar tendinopathy. Athletes with scores higher than 95 points on the Victorian Institute of Sport Assessment-patella (VISA-P), no pain during the single-leg decline squat, and no history of patellar tendon pain were considered not to have patellar tendinopathy. Classification and regression tree analyses were performed to identify interacting factors associated with patellar tendinopathy. Results Interactions among passive hip internal rotation ROM, shank-forefoot alignment, and hip external rotator and abductor strength identified athletes with and without patellar tendinopathy. The model achieved 71.2% sensitivity and 74.4% specificity. The area under the receiver operating characteristic curve was 0.77 (95% confidence interval: 0.70, 0.84; P<.001). Conclusion Impairments of the hip and foot/ankle are associated with the presence of patellar tendinopathy in volleyball and basketball athletes. Future studies should evaluate the role of these impairments in the etiology of patellar tendinopathy. J Orthop Sports Phys Ther 2018;48(9):676-684. Epub 23 May 2018. doi:10.2519/jospt.2018.7426.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".