Arthroscopic meniscal surgery vs non-operative treatment for degenerative tears with mechanical symptoms: 5-year outcomes systematic review and meta-analysis of RCTs
Bibliographic record
Abstract
The optimal management of degenerative meniscal tears with mechanical symptoms remains debated. This systematic review compares long-term outcomes of arthroscopic meniscal surgery (AMS) versus non-operative management. A search of MEDLINE, Embase, Cochrane CENTRAL, Web of Science and ClinicalTrials.gov identified RCTs (2000–2024) with ≥5 years follow-up and meta-analyses were performed. Primary outcomes were patient-reported outcome measures (PROMs) measuring knee function, activity measures and meniscal evaluation (Lysholm Knee Scoring Scale, Tegner Activity Scale, International Knee Documentation Committee score (IKDC) and Western Ontario Meniscal Evaluation Tool (WOMET)); and general health and pain measures (European Quality of Life (EuroQoL) and Visual Analog Scale (VAS)). Secondary outcomes were Knee injury and Osteoarthritis Outcome Score (KOOS) and osteoarthritic progression rate. A prospective protocol was registered on PROSPERO (CRD42023427339). Six studies (n = 1157) met the inclusion criteria. Meta-analysis showed non-significant difference in knee function, activity and meniscal evaluation (Lysholm: p=0.07; Tegner: p=1.00; IKDC: p=0.46; WOMET: p=0.77) and small difference in general health and pain (EQ-5D: p=0.26; EQ-VAS: p<0.00001; VAS: p=0.16). No significant differences were seen in KOOS (p>0.26), but osteoarthritis progression was significantly higher in surgical group (p<0.0001). There is no significant difference between AMS and non-operative management in PROMS at 5-year follow-up period in activity or pain in patients with degenerative meniscal tears with mechanical symptoms. However, patients undergoing surgery show a significantly higher osteoarthritic progression rates long-term which is essential to consider for knee function and decision-making between the two treatment groups.
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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 | 0.017 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.037 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".