Do Recreational Athletes Benefit From a Structured, High-Intensity Rehabilitation Program Post-ACL Reconstruction? A Randomized Clinical Trial
Bibliographic record
Abstract
OBJECTIVE: To compare the effectiveness of a structured high-intensity program (Rouge & Or [R&O]), which focuses on athletics abilities to facilitate return to sport, with usual care during the later phase of anterior cruciate ligament (ACL) reconstruction rehabilitation, in terms of symptoms and disability, and return to sport among recreational athletes. METHODS: Sixty-six individuals, 3 months post-ACL reconstruction, were randomly assigned to the R&O program or usual care. The primary outcome was symptoms and disability, assessed using the Knee Outcome Survey–Activities of Daily Living Scale. The secondary outcomes were adverse events, pain, perceived level of change, psychological readiness to return to play, lower-limb strength, lower-limb functional performance, and rate of return to sport at preinjury level. Follow-ups were conducted at baseline and at 6, 9, and 12 months. A linear mixed model was used to compare the groups. RESULTS: While both groups showed progress on all outcomes ( P<.01), there were no significant between-group differences ( P>.05). There were no adverse events related to the completion of the 2 programs. CONCLUSION: The structured high-intensity program did not provide additional benefits compared to usual care. However, the R&O program was a standardized and safe intervention to guide recreational athletes following ACL reconstruction. JOSPT Open 2025;3(4):483-491. Epub 18 June 2025. doi:10.2519/josptopen.2025.0091
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".