Step It Up to Level Up: After Anterior Cruciate Ligament Reconstruction, Do Individuals Reach Internationally Recommended Physical Activity Levels and How Do These Levels Compare With Uninjured Controls? A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
OBJECTIVE: Anterior cruciate ligament reconstruction (ACLR) leads to high rates of knee post-traumatic osteoarthritis (PTOA). Physical activity may mitigate PTOA risk but levels after ACLR have not been extensively studied. We aimed to review self-reported and device-measured physical activity levels in individuals with ACLR and compare them with international guidelines, and with uninjured controls. DATA SOURCES: MEDLINE, Embase, Scopus, Google Scholar, Cochrane Library, Web of Science, and SPORTDiscus were searched from inception to 22 June 2023. MAIN RESULTS: Of the 5391 studies identified on our initial search, 15 satisfied the inclusion criteria for analysis (N = 544 individuals with ACLR). Across all studies, the average physical activity levels for individuals with ACLR were 343 ± 185 moderate-to-vigorous physical activity (MVPA) min/wk and 8453 ± 233 steps/day. In studies measuring the proportion of individuals with ACLR reaching MVPA guidelines, 147/213 (69%) achieved ≥150 min/wk. Of those using step counts, 22/85 (26%) achieved ≥10 000 steps/day. Individuals with ACLR engaged in less physical activity than uninjured controls (SMD = -0.37 [95% CI = -0.60 to -0.15]; P < 0.001). CONCLUSIONS: Individuals typically meet recommended MVPA, but not steps, after ACLR. Optimal volume, type, and weight-bearing nature of physical activity should be further investigated given the beneficial role of moderate mechanical loading in knee health. Our findings suggest that steps per day may represent a potentially modifiable prevention target and may help guide the future development of tailored physical activity guidelines for PTOA prevention after ACLR. PROSPERO REGISTRATION NUMBER: CRD42022330699.
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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 | 0.012 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.031 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".