The repair of horizontal cleavage tears yields higher complication rates compared to meniscectomy: a systematic review
Bibliographic record
Abstract
PURPOSE: Horizontal cleavage tears of the meniscus (HCTs) are primarily degenerative in nature, and, however, can be the result of trauma. Such tears account for 12-35% of all tear patterns and can be treated by partial meniscectomy or arthroscopic repair. The purpose of this review was to systematically assess the outcomes and complications for patients undergoing the surgical treatment of HCTs. METHODS: This review has been conducted according to the guidelines of Preferred Reporting Items for Systematic Reviews and Meta-analyses. The electronic databases PubMed, MEDLINE, and EMBASE were searched from data inception to December 30, 2018 for articles addressing the surgical treatment of HCTs. The Methodological Index for Non-randomized Studies was used to assess study quality. Data are presented descriptively. RESULTS: Overall, 23 studies were identified, comprising of 702 patients (708 knees) with a mean age of 36.6 ± 9.9 years and a mean follow-up of 33.6 ± 19.6 months. The majority of patients were treated with a partial meniscectomy (59.0%), followed by repair (32.8%) and total meniscectomy (8.2%). Both meniscectomy and repair patients had improvements which surpassed minimal clinically important differences with regard to clinical (e.g. pain, function, daily living) and radiographic outcomes. The overall complication rate was 5.1%, primarily involving patients undergoing meniscal repair (12.9% of all knees undergoing a repair). CONCLUSION: Although meniscal repair theoretically may provide improvement in biomechanical loading, patients undergoing repair had higher complication rates than those undergoing partial meniscectomy. Clinicians should consider the available implants in determining which tear patterns to repair and future studies with long-term follow-up are needed to investigate complications (e.g. secondary meniscal procedures) as well as the potential for delay in the development of osteoarthritis. LEVEL OF EVIDENCE: Level IV.
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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 | 0.010 | 0.047 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.012 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 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".