Outcomes, Complications, and Reoperations After Meniscal Allograft Transplantation
Bibliographic record
Abstract
Background: Outcomes following meniscal allograft transplantation (MAT) are an evolving topic. Purpose: To review clinical outcomes in younger, previously active patients who underwent an isolated MAT or MAT plus any osteotomy. Concurrent surgeries, complications, and graft survivorship are presented. Study Design: Case series; Level of evidence, 4. Methods: Inclusion criteria included having undergone MAT with a minimum of 1 year of follow-up with at least 1 of the following patient-reported outcome (PRO) measures collected pre- and postoperatively: visual analog scale for pain, Knee injury and Osteoarthritis Outcome Score (KOOS), the Western Ontario and McMaster Universities Arthritis Index, the 36-Item Short Form Health Survey, and overall satisfaction. From patient records, we recorded descriptive data, side (medial/lateral), previous or concurrent procedures, perioperative complications, revisions, and conversion to arthroplasty. Two-factor analysis of variance (ANOVA) was used to test for differences in age and body mass index (BMI). A 2 × 2 chi-square test was used to determine if the spectrum of procedures performed on our study's patient group was representative of the entire population. PRO results were analyzed using a multivariate ANOVA. Results: ≤ .003); effect sizes were moderate and large. KOOS Pain and KOOS Activities of Daily Living showed some main or interaction effects that were trivial or small. Patient satisfaction with the treatment was ≥7 out of 10 in 85% of patients. A minimum of 1 subsequent surgery for various concerns was necessary in 23% of the 93 knees. Graft survival in the included patients was 100%. Conclusion: Complications (conditions requiring at least 1 subsequent surgery) affected about one-quarter of the patients who underwent MAT. Nevertheless, MAT seemed to provide our patients with adequate pain relief and improved function.
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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) | 0.000 | 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) | 0.001 | 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".