Tale of quadriceps and hamstring muscle strength after ACL reconstruction: a systematic review with longitudinal and multivariate meta-analysis
Bibliographic record
Abstract
OBJECTIVE: This study aimed to investigate how knee extensor and flexor strength change over time after anterior cruciate ligament reconstruction (ACLR). DESIGN: Systematic review with longitudinal meta-analysis. DATA SOURCES: Medline, Embase, CINAHL, Scopus, Cochrane CENTRAL and SPORTDiscus to 28 February 2023. ELIGIBILITY CRITERIA: Studies of primary ACLR (n≥50), with mean participant age 18-40 years, reporting a quantitative measure of knee extensor or flexor strength were eligible. Muscle strength had to be reported for the ACL limb and compared with: (1) the contralateral limb (within-person); and/or (2) an uninjured control limb (between-person). RESULTS: We included 232 studies of 34 220 participants. Knee extensor and flexor strength showed sharp initial improvement postoperatively before tailing off at approximately 12-18 months post surgery with minimal change thereafter. Knee extensor strength was reduced by more than 10% compared with the contralateral limb and approximately 20% compared with uninjured controls at 1 year for slow concentric, fast concentric and isometric contractions. Knee flexor strength showed smaller deficits but was still 5%-7% lower than the contralateral limb at 1 year for slow concentric, fast concentric and isometric contractions. Between-person comparisons showed larger deficits than within-person comparisons. CONCLUSION: Knee extensor muscle strength is meaningfully reduced (>10%) at 1 year, with limited improvement after this time up to and beyond 5 years post surgery. Many people likely experience persistent and potentially long-term strength deficits after ACLR. Comparison within person (to the contralateral limb) likely underestimates strength deficits in contrast to uninjured controls.
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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 | 0.019 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.040 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".