In‐Office Needle Arthroscopy: A Systematic Review of Indications and Clinical Utility
Bibliographic record
Abstract
PURPOSE: This review explores the current literature regarding both the clinical indications and utility of minimally invasive in-office needle arthroscopy (IONA) relative to conventional imaging modalities. METHODS: In compliance with R-AMSTAR (Revised Assessment of Multiple Systematic Reviews) and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines, 3 databases (MEDLINE, Embase, and PubMed) were searched in July 2018, in addition to the conference abstract databases of 5 prominent meetings between 2013 and 2018, for studies using IONA for diagnostic purposes. Study quality was assessed with the Methodological Index for Non-Randomized Studies (MINORS) criteria. RESULTS: Among 932 conference abstracts and 369 studies identified, 11 publications involving 404 patients (395 knees and 9 shoulders) were included, with 9 clinical studies and 2 cost analyses. The median Methodological Index for Non-Randomized Studies (MINORS) score was 9 for noncomparative and 23 for comparative studies. Among the 9 clinical studies, IONA had a superior sensitivity, specificity, positive predictive value, and negative predictive value to magnetic resonance imaging (MRI) in the evaluation of knee osteoarthritis, anterior cruciate ligament insufficiency, and meniscal tears. IONA was comparable or inferior to MRI in the same parameters for the diagnosis of osteochondral defects and rotator cuff tears. In the 2 cost analyses, IONA had lower costs when used in place of MRI for treatment algorithms involving medial meniscal tears and rotator cuff tears but not lateral meniscal tears. CONCLUSIONS: IONA holds potential for cost savings and improved diagnostic accuracy relative to MRI, primarily for intra-articular meniscal, ligamentous, and chondral defects of the knee. However, its current indications for use in other joints are limited to rotator cuff tears in the shoulder, making its diagnostic value in other joints much more limited. The current quality and breadth of evidence are significantly lacking, with numerous practical shortcomings. To improve acceptance of IONA, priority should be placed on establishing defined protocols, indications, contraindications, and patient perspectives for the procedure. LEVEL OF EVIDENCE: Level IV, systematic review of Level II, III, and IV studies.
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How this classification was reachedexpand
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".