Functional knee brace use effect on peak vertical ground reaction forces during drop jump landing
Bibliographic record
Abstract
PURPOSE: The aim of the study was to investigate the landing strategies used by non-injured athletes while wearing functional knee braces (FKB, BR condition) during a drop jump task compared with non-injured, non-braced (NBR condition) subjects and also to ascertain whether accommodation to a FKB was possible by non-injured BR subjects. METHODS: Twenty-three healthy male provincial and national basketball and field hockey athletes (age, 19.4 ± 3.0 years) were tested. Each subject was provided with a custom-fitted FKB. Five NBR testing sessions were performed over 3 days followed by five BR testing sessions also over 3 days, for a total of 17.5 h of testing per condition. Each subject performed eight trials of the drop jump task during each testing session per condition. Single-leg peak vertical ground reaction forces (PVGRF) and the time to PVGRF were recorded for each NBR and BR trail. RESULTS: The BR group mean PVGRF at landing was significantly lower (1,628 ± 405 N, 2.1 ± 0.5 BW versus 1,715 ± 403 N, 2.2 ± 0.5 BW, F (1,22) = 6.83, P = 0.01) compared with NBR subjects, respectively. The group mean time to PVGRF was not statistically longer during the BR condition (F (1,22) = 0.967, P = 0.3). Further, an accommodation trend was noted as percent performance difference decreased with continued FKB use. CONCLUSIONS: The significantly lower group mean PVGRF while using a FKB could keep traumatic forces from reaching the ACL until the active neuromuscular restraints are activated to provide protection to the knee joint ligaments. Also, accommodation to FKB is possible after approximately 14.0 h of brace use. The results of this paper will assist clinicians in providing information to their patients regarding a FKB ability to offer protection to an ACL-deficient knee or to address concerns about early muscle fatigue, energy expenditure, heart rate, and decrease in performance level. LEVEL OF EVIDENCE: Prospective study, Level I.
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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 | 0.000 |
| 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".