Knee laxity, joint hypermobility, femoral anteversion, hamstring extensibility and navicular drop as risk factors for non‐contact anterior cruciate ligament injury in female athletes: A 4.5‐year prospective cohort study
Bibliographic record
Abstract
PURPOSE: To investigate whether six selected anatomical variables were associated with non-contact anterior cruciate ligament (ACL) injury in female team sport athletes. METHODS: Two hundred eighty-seven female athletes (age 13-38 at baseline) from basketball, floorball, ice hockey and volleyball completed a baseline physical examination, including measurements of anterior-posterior (AP) knee laxity, knee hyperextension, generalized joint hypermobility, femoral anteversion, hamstring extensibility and navicular drop. Athletes entered the study either in 2011, 2012 or 2013 and were followed up until the end of 2015. During the follow-up, all complete and magnetic resonance-verified ACL injuries were recorded. RESULTS: Twenty-three non-contact ACL injuries were recorded. There were no significant differences in baseline physical examination variables between athletes who sustained ACL injuries and those who did not. However, a side-to-side difference in AP knee laxity greater than 2 mm was observed in 20% of the ACL injury group compared to 12% of the non-injured group, although this difference was not statistically significant. CONCLUSIONS: In this study, AP knee laxity, knee hyperextension, generalized joint hypermobility, femoral anteversion, hamstring extensibility and navicular drop were not associated with increased risk for non-contact ACL injury in female team sport athletes. This study was powered to detect moderate to strong risk associations; thus, smaller risk associations may not have been identified. LEVEL OF EVIDENCE: Level II.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".