Over 90 % of children and adolescents return to sport after anterior cruciate ligament reconstruction: a systematic review and meta-analysis
Bibliographic record
Abstract
PURPOSE: To evaluate the rate at which children and adolescent athletes return to sporting activities after anterior cruciate ligament (ACL) reconstruction. METHODS: Three databases, PubMed, MEDLINE, and EMBASE, were searched from database inception until September 9, 2017 by two reviewers independently and in duplicate. The inclusion criteria were English language studies that reported return to sport outcomes. Book chapters, conference papers, review articles, and technical reports were excluded. The rate of return to sports was combined in a meta-analysis of proportions using a random-effects model. RESULTS: Overall, 20 studies with a combined total of 1156 ACL reconstructions met the inclusion criteria, with a mean age of 14.3 years (range 6-19) and a mean follow-up time of 6.5 years (range 1-22). All studies were level IV evidence (14 retrospective case series and 6 prospective case series). The pooled rate of return to any sport participation was 92.0% [95% confidence interval (CI), 86-96%]. The pooled rate of return to pre-injury level of sport was 78.6% (95% CI 71-86%) and that to competitive level of sport was 81.0% (95% CI 62-94%). A total of 93 of the 717 assessed athletes (13%) sustained re-injuries with graft ruptures, and in 91 of 652 patients (14%), contralateral ACL injuries were reported on final follow-up. CONCLUSION: Pooled results suggest a high rate of return to sport following ACL reconstruction in children and adolescent athletes; however, this is associated with a relatively high rate of graft rupture and a similar rate of contralateral ACL injury. This study provides clinicians with evidence-based data on the ability of children and adolescent athletes to return to sport after ACL reconstruction, an important consideration for athletes of this population with ACL injuries. LEVEL OF EVIDENCE: IV, systematic review of level IV studies.
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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 | 0.016 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.032 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| 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".