The Relationship Between Isokinetic Hamstring To Quadriceps Strength Ratio And A Battery Of Exercise Field Tests In Healthy Women
Bibliographic record
Abstract
Knee injuries are one of the most common ball sport related injuries and cause hundreds of millions of dollars in rehabilitation costs annually. Girls and women are 4-9 times more likely to experience a knee injury compared to boys and men, and typically suffer more severe knee injuries. Strength imbalance of the hamstrings and quadriceps muscles during complex sport movements and/or as a result of fatigue may contribute to knee injury occurrence. PURPOSE: This study attempted to predict the ratio of isokinetic muscular strength of the hamstring and quadriceps muscles from a battery of exercise field tests both before and after fatigue. METHODS: Women (n = 29) were recruited from the University of Windsor and completed an exercise field testing protocol consisting of a 20m forward sprint, 20m backward sprint, 5-10-5 agility test, single leg hop for distance, side hop, vertical jump, and eccentric Nordic hamstring curl (NHC), as well as an isokinetic dynamometer protocol to obtain muscle peak torques (PT) and hamstring to quadricep PT ratios (HQR), before and after a 45 minute simulated exercise protocol. RESULTS: PT (F(1,228) = 27.678, p =0.00) and HQR (F(1.871,321.889)= 15.689, p =0.00) decreased following the exercise protocol. Further, the battery of field tests were able to predict HQRcon/con at 60o in the non-dominant limb (F(3,24) = 4,42, R2 = 0.622 p = 0.015), with a combination of the speed tests (ST), jump tests (JT) and NHC in the final model, but not changes that occurred because of the exercise protocol. CONCLUSION: HQR may predict knee injury risk, and consequently, the field tests employed in the current study could be used by strength and conditioning specialists to assess risk without the need for more expensive equipment. However, HQR should be reassessed as a method for knee injury prediction with respect to more functional models, at specific joint angles, and in relation to fatigue. Further, future studies should employ additional field tests that may strengthen the association with risk.
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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 | 0.000 | 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".