Corticospinal and intracortical excitability in individuals with anterior cruciate ligament injury and ligament reconstruction: a meta-analysis
Bibliographic record
Abstract
Background Primary motor cortex (M1) organization and quadriceps femoris excitability may change after anterior cruciate ligament injury (ACLi) and anterior cruciate ligament reconstruction (ACLr), as demonstrated by transcranial magnetic stimulation (TMS) studies.Objective To systematically review studies evaluating changes in quadriceps femoris corticospinal and intracortical excitability in subjects with ACLi and ACLr.Methods Database searches were conducted in PubMed, Embase, Scopus, and ScienceDirect, with the last search performed on November 23, 2023. Newcastle-Ottawa Scale and a specific checklist for evaluating descriptions in studies using TMS assessment were used. Continuous variables were expressed as mean and standard deviation and represented by the estimated difference from the mean and 95% confidence interval (CI). Heterogeneity was assessed by Chi2 and I2 and the level of statistical significance was 5%.Results Fourteen studies, comprising 381 individuals, using TMS were identified. Meta-analysis results showed significantly higher motor threshold (MT) in ACLi/ACLr individuals compared to healthy controls (p < .01, mean difference 6.72). Additionally, MTs were significantly higher on the uninjured side compared to healthy controls (p < .0001, mean difference 3.82). Motor-evoked potentials (MEP) amplitude was significantly higher on the uninjured side compared to the injured side (p < .00001, mean difference 0.01). Short-interval intracortical inhibition (SICI) amplitude was significantly lesser on the injured limb compared to the uninjured side (p < .00001, mean difference 0.50).Conclusion Quadriceps MT and SICI are altered in ACLi and ACLr populations, and minor alterations were identified in MEP, demonstrating brain changes related to anterior cruciate ligament injury and/or reconstruction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.038 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".