Anterior cruciate ligament reconstruction improves subjective ability but not neuromuscular biomechanics during dynamic tasks
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to identify high-functioning anterior cruciate ligament-deficient patients and assess the effects of reconstruction on their self-reported functionality, muscle activations and biomechanical properties. METHODS: Twenty young and active patients participated pre- (11.5 ± 14.3 months post-injury) and again 10.5 ± 1.7 months post-reconstruction and were individually matched to 20 healthy controls. Participants completed hop and side cut movements while patient-related outcome measures, lower limb electromyography, kinetic, and whole body kinematic data were collected. One-dimensional statistical parametric mapping was used to test for group differences (healthy vs deficient; deficient vs reconstructed; reconstructed vs healthy). RESULTS: When comparing healthy to anterior cruciate ligament-deficient participants, all questionnaires indicated significant lower subjective function while the only substantial biomechanical difference between these participants was a decreased knee extensor moment in both the hop (peak difference: 0.63 Nm/kg, p < 0.001) and side cut (peak difference: 0.76 Nm/kg, p < 0.001). When comparing patients' pre- and post-reconstruction, no biomechanical differences were observed whereas only half of the questionnaires (Tegner, Lysholm, KNEES-ADL, KNEES-Slackness, KNEES-Looseness, KNEES-Sport Behaviour, IKDC, and KOOS-QoL) indicated higher function in the reconstructed state. When comparing the reconstructed patients to the healthy participants, all questionnaires were still significantly higher in the healthy controls. The reconstructed group also had a smaller flexion angle (peak difference: 14.5°, p = 0.007) and knee extensor moment (peak difference: 0.62 Nm/kg, p < 0.001) during the hop and a smaller knee extensor moment (peak difference: 0.90 Nm/kg, p < 0.001) during the side-cut task. CONCLUSION: At 10-months post-reconstruction, the current results indicate that in high-functioning anterior cruciate ligament-deficient patients, reconstruction had little impact on objective measures of functional ability during dynamic tasks although self-reported function was improved. LEVEL OF EVIDENCE: Therapeutic prospective cohort study, 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 | 0.000 |
| 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) | 0.003 | 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".