Ankle perturbation generates bilateral alteration of knee muscle onset times after unilateral anterior cruciate ligament reconstruction
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to compare muscle activation onset times of knee muscles between the involved and uninvolved knee of patients with unilateral anterior cruciate ligament reconstruction (ACLR), and the uninjured knees of healthy subjects after a controlled perturbation at the ankle level. METHODS: Fifty male amateur soccer players, 25 with unilateral ACLR using semitendinosus-gracilis graft (age = 28.36 ± 7.87 years; time after surgery = 9 ± 3 months) and 25 uninjured control subjects (age = 24.16 ± 2.67 years) participated in the study. Two destabilizing platforms (one for each limb) generated a controlled perturbation at the ankle of each participant (30°of inversion, 10°plantarflexion simultaneously) in a weight bearing condition. The muscle activation onset times of semitendinosus (ST) and vastus medialis (VM) was detected through an electromyographic (EMG) analysis to assess the neuromuscular function of knee muscles. RESULTS: Subjects with ACLR had significant delays in EMG onset in the involved (VM = 99.9 ± 30 ms; ST = 101.7 ± 28 ms) and uninvolved knee (VM = 100.4 ± 26 ms; ST = 104.7 ± 28 ms) when compared with the healthy subjects (VM = 69.1 ± 9 ms; ST = 74.6 ± 9 ms). However, no difference was found between involved and uninvolved knee of the ACLR group. DISCUSSION: The results show a bilateral alteration of knee muscles in EMG onset after a unilateral ACLR, responses that can be elicited with an ankle perturbation. This suggests an alteration in the central processing of proprioceptive information and/or central nervous system re-organization that may affect neuromuscular control of knee muscles in the involved and uninvolved lower limbs.
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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".