Time to be honest regarding outcomes of ACL reconstructions: should we be quoting 55–65% success rates for high-level athletes?
Bibliographic record
Abstract
Five to ten years ago it was common for orthopaedic surgeons to assure their ACL injured patients that 90–95% of the time they would have a good to excellent result with surgical reconstruction. We suspect that such advice can still be heard in orthopaedic offices. However, recent studies evaluating return to play, recurrent or contralateral ACL injuries, and specific graft choices, have raised concern that the picture we were painting may have been too rosy. Walden et al 1 present their outcomes of a prospective study on football (soccer) players regarding actual return to play rates. The authors followed 78 elite soccer clubs for 4 years and reported 140 complete ACL injuries (98% that underwent reconstruction). Surprisingly, prior to completing rehabilitation, five patients had reruptures and four required contralateral ACL surgery. At 3 years, 86% of patients were still playing football but only 65% were playing at …
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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 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.014 | 0.026 |
| Insufficient payload (model declined to judge) | 0.004 | 0.006 |
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".