Long‐Term Survival Analysis and Outcomes of Meniscal Allograft Transplantation With Minimum 10‐Year Follow‐Up: A Systematic Review
Bibliographic record
Abstract
PURPOSE: To investigate the long-term survivorship rates and functional outcomes of meniscal allograft transplantation (MAT) in patients with minimum 10-year postoperative follow-up. METHODS: Two reviewers independently searched EMBASE, MEDLINE, and PubMed from database inception for literature related to MAT according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. Data are reported in a narrative summary fashion with descriptive statistics. RESULTS: Eleven studies with a total of 658 patients and 688 MATs were included. Mean age of patients was 33.1 years (range 14-66), of whom 63% were male. Mean survivorship rates were 73.5% at 10-year and 60.3% at 15-year follow-up, with 2 studies reporting 19- and 24-year survivorship of 50% and 15.1%, respectively. Pre- and postoperative Lysholm scores ranged from 36 to 60.5 and 61 to 75, respectively. Pre- and postoperative Tegner scores ranged from 1 to 3 and 2.5 to 4.6, respectively. Postoperative Knee injury and Osteoarthritis Outcome Score subset scores were as follows: Pain: 61.6 to 76.3; Symptoms: 57.9 to 61.8; Function in Daily Living: 68.5 to 79.9; Sport and Recreation: 33.9 to 49.3; Quality of Life: 37.3 to 45.9. Postoperative International Knee Documentation Committee scores ranged from 46 to 77. Regarding surgical technique, 194 MAT bone-fixation technique (53.8%) and 165 MAT suture-only fixation techniques (46.2%) were reported. The most common type of allograft used was cryopreserved (54.5% of the allografts). The most frequent concomitant procedures performed with MAT were to address chondral (20.8% of the cases) and ligament injuries (12.4% of the cases), and realignment procedures (9.4% of the cases). The most common complications observed that were not directly related to concomitant procedures were meniscal allograft partial tears (11.1%), arthrofibrosis (3.6%), and infection (2.0%). Several criteria were used among studies to define failure of MAT, the most common parameters being removal of meniscal allograft (8/11 studies) and conversion to total knee arthroplasty (7/11 studies). CONCLUSIONS: MAT can yield good long-term survivorship rates, with 73.5% and 60.3% of allografts remaining functional after 10 and 15 years, respectively. Functional outcomes 10 years after MAT were fair and improved compared with preoperative scores. LEVEL OF EVIDENCE: Level IV, systematic review of Level III and IV studies.
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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 | 0.009 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.015 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".