Meniscal transplantation: state of the art
Bibliographic record
Abstract
Meniscal resection is the most common surgical procedure in orthopaedics. When a large meniscal loss becomes clinically relevant, meniscal allograft transplantation (MAT) is a feasible option. However, although this technique has evolved since the '80s, there are still several controversial issues related to MAT. Most importantly, its chondroprotective effect is still not completely proven. Its relatively high complication and reoperation rate is another reason for this procedure not yet being universally accepted. Despite its controversial chondroprotective effect, nevertheless, MAT has become a successful treatment for pain localised in a previously meniscectomised knee, in terms of pain relief and knee function. We conducted a careful review of the literature, highlighting the most relevant studies in various aspects of this procedure. Precise indications, how it behaves biomechanically, surgical techniques, return to sport and future perspectives are among the most relevant topics that have been included in this state-of-the-art review. Meniscal resection is the most common surgical procedure in orthopaedics. When a large meniscal loss becomes clinically relevant, meniscal allograft transplantation (MAT) is a feasible option. However, although this technique has evolved since the '80s, there are still several controversial issues related to MAT. Most importantly, its chondroprotective effect is still not completely proven. Its relatively high complication and reoperation rate is another reason for this procedure not yet being universally accepted. Despite its controversial chondroprotective effect, nevertheless, MAT has become a successful treatment for pain localised in a previously meniscectomised knee, in terms of pain relief and knee function. We conducted a careful review of the literature, highlighting the most relevant studies in various aspects of this procedure. Precise indications, how it behaves biomechanically, surgical techniques, return to sport and future perspectives are among the most relevant topics that have been included in this state-of-the-art review.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".