Synthetic medial meniscus implant demonstrates high reoperation rates: Patients who retain implant or require implant exchange show improvement in post meniscectomy knee pain and clinical function
Bibliographic record
Abstract
PURPOSE: To evaluate the clinical outcomes in the use of a synthetic medial meniscus implant in patients symptomatic after medial meniscectomy and not responsive to nonoperative treatment. METHODS: This single-arm, multicenter, prospective study enrolled subjects between ages 30 and 75 with postmeniscectomy pain. Changes from baseline to 24 months were measured in the pain subscale of the knee injury and osteoarthritis outcome score (KOOS) and in KOOS overall (average of all 5 subscales) in patients that had received a medial meniscus implant. Success was a 20-point improvement at 24 months, and reoperation rates and implant failures were recorded. Visual Analog Scale, International Knee Documentation Committee, and Western Ontario Meniscal Evaluation Tool scores were also measured. RESULTS: Of the 115 treated patients, 3 (2.6%) were either lost to follow-up or missed the 24-month visit, 48 (43%) patients had at least 1 subsequent surgery, and 12 (10.7%) had the implant permanently removed. Of the remaining 100 patients, the mean KOOS pain improved 28.4 points at 24 months (P < .001), and the mean KOOS overall improved 28.3 points (P < .001). Of the subjects, 76% had mean scores for KOOS pain above the minimal clinically important difference threshold, and 72% of subjects met or exceeded this threshold for KOOS overall. There were 29 patients (25.9%) who underwent implant exchange. The 24-month clinical outcomes were similar between subjects who had an implant exchange and patients who did not have any subsequent implant procedure (P < .2). CONCLUSIONS: The synthetic medial meniscus implant shows high reoperation and failure rates. Patients who retained the implant or required implant exchange showed improved pain and function.
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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 | 0.002 |
| 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 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".