Hop to It! A Systematic Review and Longitudinal Meta-analysis of Hop Performance After ACL Reconstruction
Bibliographic record
Abstract
BACKGROUND: Hop testing is widely used by clinicians to monitor rehabilitation and decide when to return to sport following anterior cruciate ligament reconstruction (ACLR); however, the trajectory of long-term hop performance has not been summarised. OBJECTIVE: To investigate hop performance change over time after 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 with ≥ 50 participants following primary ACLR, with mean participant age of 18-40 years, reporting a quantitative measure of hop performance (e.g. single forward hop distance). Results had to be reported for the ACLR limb and compared with (1) the contralateral limb (within person) and/or (2) an uninjured control limb (between person). RESULTS: We included 136 studies of 23,360 participants. Performance was similar across different hop tests, with steep initial improvements in within-person symmetry, tailing off after 18-24 months. ACLR limb hop performance was 5-10% lower compared with the contralateral limb at 1 year post-surgery, with largest deficits observed for vertical hop [87.0% contralateral limb (95% CI 85.3-88.8) compared with single forward hop 93.8% (95% CI 92.8-94.9)]. By 3-5 years, results were similar between ACLR and contralateral limbs. There were limited data for between-person comparisons (n = 17 studies). Exploratory analyses showed deficits in all forward hopping tests to be very strongly correlated with each other [e.g. single forward and triple hop rho = 0.96 (95% CI 0.90-0.99)], though there was discordance in the relationship between single forward hop and vertical hop performance [rho = 0.27 (95% CI - 0.53 to 0.79)]. CONCLUSIONS: Hop performance is comparable to the uninjured limb by 3-5 years post-ACLR, with the greatest deficits in within-person symmetry present in vertical and side hop tests. Assessment of hopping in multiple planes and comparison with uninjured controls, may provide the most complete evaluation of functional performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.015 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| 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 teacher head, 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".