Meniscal repair at the time of primary ACLR does not negatively influence short term knee stability, graft rupture rates, or patient‐reported outcome measures: the STABILITY experience
Bibliographic record
Abstract
PURPOSE: To assess how meniscal repair and excision impact short term patient-reported outcome measures (PROMs), knee stability, and early graft rupture rates following primary hamstring anterior cruciate ligament reconstruction (ACLR) with or without lateral extra-articular tenodesis (LET) in a group of young active patients where meniscal repair is commonly advocated. METHODS: Six hundred and eighteen patients under 25 years of age at high-risk of graft failure following ACLR were recruited to the Stability 1 study. Multivariable regression models were developed to identify statistically and clinically significant surgical and demographic predictors of Knee Injury and Osteoarthritis Outcome Score (KOOS), International Knee Documentation Committee Subjective Knee Form (IKDC), ACL Quality of Life Questionnaire (ACL-QOL) and Marx Activity Rating Scale (MARS) scores. Chi-Square tests of independence were used to explore the association between meniscal status (torn, not torn), meniscal treatment (excision or repair), graft rupture, and rotatory knee laxity. RESULTS: Medial meniscus repair was associated with worse outcomes on the KOOS (β = -1.32, 95% CI: -1.57 to -1.10, p = 0.003), IKDC (β = -1.66, 95% CI: -1.53 to -1.02, p = 0.031) and ACL-QOL (β = -1.25, 95% CI: -1.61 to 1.02, p = n.s.). However, these associations indicated small, clinically insignificant changes based on reported measures of clinical relevance. Other important predictors of post-operative PROMs included age, sex, and baseline scores. Medial meniscus excision and lateral meniscus treatment (repair or excision) did not have an important influence on PROMs. There was no significant association between meniscal treatment and graft rupture or rotatory knee laxity. CONCLUSION: While repairing the medial meniscus may result in a small reduction in PROM scores at two-year follow-up, these differences are not likely to be important to patients or clinicians. Any surgical morbidity associated with meniscal repair appears negligible in terms of PROMs. Meniscal repair does not affect rotatory laxity or graft failure rates in the short term. Therefore, meniscal repair should likely be maintained as the standard of care for concomitant meniscal tears with ACLR. LEVEL OF EVIDENCE: III.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".