Rapid Hamstrings/Quadriceps Strength in ACL-Reconstructed Elite Alpine Ski Racers
Bibliographic record
Abstract
PURPOSE: Because of the importance of hamstrings (HAM) and quadriceps (QUAD) strength for anterior cruciate ligament (ACL) injury prevention and the high incidence of ACL injury in ski racing, HAM and QUAD maximal and explosive strength were assessed in ski racers with and without ACL reconstruction (ACL-R). METHODS: Uninjured (n = 13 males, n = 8 females) and ACL-R (n = 3 males, n = 5 females, 25.0 ± 11.3 months after operation) elite ski racers performed maximal voluntary isometric HAM and QUAD contractions to obtain maximal torque (MVC) and rate of torque development (RTD) at 0-50, 0-100, 0-150, and 0-200 ms. MVC and RTD (per kilogram body mass) were calculated for the uninjured group to compare between sexes and to compare the control group with the ACL-R limb and unaffected limb of the ACL-R skiers. HAM/QUAD MVC and RTD strength ratios (H/Q ratios) were also compared. RESULTS: The ACL-R limb demonstrated significant HAM and QUAD deficits compared with the contralateral limb for MVC and late-phase RTD (P < 0.05). Uninjured male skiers also displayed a limb difference for HAM MVC and RTD at 150 ms (P < 0.05). QUAD MVC and RTD deficits were observed in the affected limb of ACL-R skiers, which led to an inflated H/Q ratio (50 ms) compared with that in uninjured controls (P < 0.05). Compared with male skiers, females displayed greater relative HAM RTD (50 ms) and an elevated H/Q RTD ratio (50 ms), suggesting enhanced ACL protection (P < 0.05). CONCLUSIONS: Because of the strength demands of ski racing, our results suggest the importance of including HAM and QUAD strength assessments in the physical evaluation of uninjured skiers. Furthermore, HAM and QUAD strength should be assessed over a long-term period after surgery to identify chronic strength deficits in ACL-R ski racers.
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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 | 0.000 |
| 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".