A systematic review to evaluate exercise for anterior cruciate ligament injuries: does this approach reduce the incidence of knee osteoarthritis?
Bibliographic record
Abstract
PURPOSE: Among a variety of conservative and surgical options to treat anterior cruciate ligament (ACL) injuries, we do not understand which options could potentially prevent knee osteoarthritis (OA). The aim of this systematic review was to examine the evidence pertaining to exercise treatment of ACL injuries in the context of knee OA. METHODS: Medline, Embase, CINAHL, PubMed, and PEDro (Physiotherapy Evidence Database) databases were systematically searched using keywords encompassed within four primary key terms: knee, osteoarthritis, anterior cruciate ligament, and exercise. Clinical studies evaluating the effect of an exercise treatment for ACL injuries on the development of knee OA in adult humans were included. The PEDro scale was used to critically assess the studies included in the review. RESULTS: Eighteen studies were included in this review, with a median PEDro score of 6/11 (range, 2/11-9/11). Three studies provided statistical evidence that exercise following ACL injury lowered the risk for knee OA development. Nine studies demonstrated no benefit of exercise in preventing knee OA incidence relative to either operative treatment or the contralateral, unaffected knee. However, exercise resulted in higher knee instability. Nonetheless, there were no significant differences in subjective or objective knee outcomes for early versus late ACL reconstruction. LIMITATIONS: This review was not registered through PROSPERO. CONCLUSION: The relationship between a rehabilitative exercise for ACL injuries and long-term knee OA prevalence is inconclusive. However, research suggests initial conservative treatment with optional late ACL reconstruction because this treatment strategy may reduce the risk of knee OA. More research, ideally randomized controlled trials or comparable designs, is required prior to establishing clinical guidelines for ACL injury management.
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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 | 0.013 | 0.054 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.008 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".