Anterior cruciate ligament reconstruction with concomitant meniscal surgery: a systematic review and meta‐analysis of outcomes
Bibliographic record
Abstract
PURPOSE: The aim of this review was to compare the clinical outcomes of anterior cruciate ligament reconstruction (ACLR) with either meniscal repair or meniscectomy for concomitant meniscal injury. The primary hypothesis was that short-term clinical outcomes (≤ 2-year follow-up) for ACLR concomitant with either meniscal repair or resection would be similar. The secondary hypothesis was that ACLR with meniscal repair would result in better longer term outcomes compared with meniscal resection. METHODS: The authors searched two online databases (EMBASE and MEDLINE) from inception until March 2018 for the literature on ACLR and concurrent meniscal surgery. Two reviewers systematically screened studies in duplicate, independently, and based on a priori criteria. Quality assessment was also performed in duplicate. The Knee injury and Osteoarthritis Outcome Score (KOOS) sub-scale scores at 2 years post-operatively were combined in a meta-analysis of proportions using a random-effects model. RESULTS: Of 2566 initial studies, 25 studies satisfied full-text inclusion criteria. Mean follow-up was 2.09 years, with a total sample of 37,087 subjects including controls. The meta-analysis demonstrated equivocal results at 2 years, except for KOOS symptom scores which favoured meniscal resection over repair. Mean KT-1000 side-to-side difference (SSD) scores were 1.51 ± 0.60 mm for meniscal repair, 1.96 ± 0.36 mm for meniscal resection, and 1.58 ± 0.20 for control patients (isolated ACLR). Medial meniscal repair showed decreased anterior knee joint laxity compared to medial meniscal resection (P < 0.001). Patients with meniscal repair had higher rates of re-operation (13.3% vs 0.8% for meniscal resection, P < 0.001). CONCLUSION: Patients with ACLR combined with meniscal resection demonstrate better symptoms at 2-year follow-up compared to patients with ACLR combined with meniscal repair. ACLR combined with meniscal repair results in decreased anterior knee joint laxity with evidence of improved patient-reported outcomes in the long term, but also higher re-operation rates. LEVEL OF EVIDENCE: III.
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 | 0.011 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.026 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".