Knee Arthroscopy for the Treatment of Lipoma Arborescens
Why this work is in the frame
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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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| 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) | 0.000 | 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 it