52 Functional Outcomes and Return to Sport Following Anterior Cruciate Ligament Reconstruction in Recreational Athletes: A Systematic Review
Bibliographic record
Abstract
Abstract Introduction Outcomes of anterior cruciate ligament reconstruction (ACLR) are well reported in athletic populations, however surprisingly little information is available for outcomes in the recreational athletes that make up the majority of cases. The aim was therefore to assess post-operative outcome and return-to-sport in recreational athletes following ACLR. Method A systematic search was conducted in Ovid MEDLINE, CINAHL, AMED and the grey literature according to the PRISMA guidelines. Studies involving a clear definition of recreational athletes who underwent ACLR and recorded postoperative outcomes were included. Publication quality was assessed using Newcastle-Ottawa Scale. Results 107 studies were identified, 19 full-text records reviewed and 13 included, reflecting 1342 patients with an average age of 31.7 (SD 9.8). Mean follow-up was 43.6-months (SD 42.8). Functional activity change was reported in 92% (12/13) papers. Functional outcome was assessed with the Tegner activity score in seven studies, with 43% (3/7) reporting a post-operative improvement. The Lyshom score was used in five, of which, 60% (3/5) showed post-operative improvement, 20% (1/5) showed no difference and 20% (1/5) showed a decrease. 69% (9/13) studies reported return-to-sport, with a mean rate of 55% (S.D. 19.2) at a mean follow-up of 32-months (SD. 34.8). Reported return-to-sports rate increased with length of follow-up. Conclusions Approximately only 50% of recreational athletes increase activity level and return-to-sport following ACLR. There is wide variation in return-to-sports timeframes reported, and the link between return-rate and post-operative timeframe suggests that longer follow-up periods may be required to accurately capture return-to-sport rates in recreational athletes.
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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 | 0.007 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.011 | 0.012 |
| 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) | 0.005 | 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".