Knee Arthroscopy for the Treatment of Lipoma Arborescens
Bibliographic record
Abstract
BACKGROUND: Lipoma arborescens is a rare, intra-articular benign lesion characterized by hyperplastic formation of villous projections that commonly presents as nonspecific mechanical knee pain. The treatment of choice for lipoma arborescens of the knee is open or arthroscopic synovectomy. However, data are lacking on the success of arthroscopic treatment, despite its increasingly widespread use. We aimed to systemically review the outcomes of arthroscopic treatment of lipoma arborescens. METHODS: PubMed and Embase were searched by 2 reviewers independently on October 9, 2018, and all relevant articles in the English and French languages up to and including that date were considered. The search terms "lipoma arborescens," "knee," "arthroscopy," and "arthroscopic" were used. Articles were screened on the basis of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. RESULTS: Among the 110 initial studies that were retrieved, 28 satisfied the inclusion criteria. A total of 71 knees in 65 patients ranging from 13 to 78 years of age underwent arthroscopic synovectomy for the treatment of lipoma arborescens. The duration of follow-up ranged from 3 weeks to 84 months. The recurrence rate was 2.8%, and 2 patients underwent conversion to open surgery. One patient had postoperative hematoma that required evacuation, and another patient reported persistent residual pain at the time of the latest follow-up. CONCLUSIONS: On the basis of this uncontrolled, systematic review, arthroscopic synovectomy is a safe and effective treatment for lipoma arborescens of the knee, with a success rate of >95%. LEVEL OF EVIDENCE: Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".