Does An Intensive Rehabilitation After ACL Reconstruction Result In Higher Full Return To Sport Rate?
Bibliographic record
Abstract
PURPOSE: Getting back to the same level of play as pre-injury is challenging for most athletes following anterior cruciate ligament reconstruction (ACLr). Data show that a third of athletes fail to reach pre-injury level after ACLr. This could be explained by the fact that the rehabilitation process is long, and often not standardized and sufficiently demanding between the 3rd and 6th month. A new intensive standardized program post ACLr (starting 3rd month post-surgery) specifically developed for football varsity athletes seems to lead to good clinical results and satisfying return to sport (RTS) rate and level. The purpose of this study was to compare, in amateur athletes, the rate of RTS at the pre-injury level between athletes completing this new program (EXP group) to the ones receiving usual rehabilitation care (URC) (CTL group). METHODS: Using a single-blind (evaluator) randomized clinical trial, 66 amateur athletes (18-35 years old; 3 months post ACLr; willing to return to sport) were randomly assigned to the EXP (aged 23.3 ± 3.25; 36.3% men) or CTL (aged 24.9 ± 4.92; 36.3% men) group. Participants of the EXP group trained with the varsity program while the CTL group received URC. The RTS rate at 1 year post ACLr was determined using two criteria; a) did they return to the same type of sport they practiced pre-injury; b) did they return at the same level of play as pre-injury. A full RTS was achieved when the answer to these 2 questions (the criteria for a return to sport to the pre-injury level) was yes. RankFD analyses were used to compare groups on full RTS 1 year after ACLr. RESULTS: There was no significant difference (p=: 0.840) in the one-year return to sport at pre-injury level between EXP (39%, 11/28 athletes) and CTL (37% - 11/30 athletes) groups. There was an overall 45% return to type 1 sports (EXP 40%, 10/25 and CTL 50%, 11/22, p = 0.198) and a 42% return to competitive or higher level (EXP 60%, 9/15 and CTL 28%, 5/18, p = 0.067). CONCLUSIONS: A new intensive rehabilitation program specifically developed for football varsity athletes does not seem to provide additional benefit regarding return to sport at pre-injury level for amateur athletes post ACLr. Further research is needed before discarding this new program since the lack of gym access and sport restriction during covid-19 pandemic might have influenced the findings.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".