Anterior Cruciate Ligament Injuries Change Muscle Co-Activation Strategies in Adolescent Females During Landing
Bibliographic record
Abstract
Background: Anterior cruciate ligament (ACL) injuries in adolescents continue to rise. Given that muscles are the only modifiable contributors to knee joint control, there has been a focus on their management in rehabilitation research. After an ACL injury, increased co-activation of the thigh muscles is considered a hallmark characteristic in stabilising the knee joint among adults with ACL injuries. However, increasing co-activation to improve joint stiffness should not be the rehabilitation goal after an ACL injury since a prolonged increase in co-activation about the joint alters knee joint loads and is associated with the onset and progression of knee osteoarthritis in adults. Purpose: Co-activation information currently does not exist among adolescents, therefore this study set out to address this gap. Methods: Twelve female patients with ACL-deficiency (ACLd) and 12 matched controls (CON) performed countermovement jumps while having the following muscle activations recorded for both limbs: rectus femoris (RF), vastus lateralis (VL), vastus medialis (VM), biceps femoris (BF), semitendinosus (ST), lateral (LG) and medial gastrocnemii (MG), and gluteus medius (GM). During the landing phase of the task, co-activation indices were calculated for the lateral thigh muscles (VL and ST), medial thigh muscles (VM and BF), and the total thigh muscles (VL&VM and BF&ST). Independent-sample t-tests ( p=.05) evaluated mean group differences for each of the three co-activation indices. Results: A significant difference was found in medial co-activation ( p=.019), while a trend towards significance ( p=.071) was found in total thigh co-activation, with ACLd females having higher co-activations indices in both compared to matched controls (Figure 1). No differences were observed between groups in their demographics or lateral co-activation indices. Conclusion: Failure to appropriately adapt one’s neuromuscular control strategies may explain why some individuals continue to have knee instability and difficulty returning to their pre-ACL injury activity levels after rehabilitation. This is evidenced by our findings among this cohort of females with ACL injuries who displayed higher co-activations, specifically in the medial thigh musculature. Moreover, our findings highlight the need to target individual muscles during rehabilitation and to avoid generalization of segment muscles (i.e. quadriceps and hamstrings) where vital information in knee joint stabilization may be missed. [Figure: see text]
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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".