Needle Diagnostic Arthroscopy and Magnetic Resonance Imaging of the Shoulder Have Comparable Accuracy With Surgical Arthroscopy: A Prospective Clinical Trial
Bibliographic record
Abstract
PURPOSE: To examine the accuracy, sensitivity, and specificity of a minimally invasive needle arthroscopy device and magnetic resonance imaging (MRI) compared with diagnostic arthroscopy, the gold standard in diagnosing intra-articular shoulder pathologies. METHODS: This was a prospective, blinded clinical trial over 6 months on 50 patients with shoulder pathology requiring arthroscopy. Patients were eligible if they had an MRI and consented for surgical arthroscopy. Patients were excluded if they didn't consent. Each underwent a clinical evaluation, MRI, needle arthroscopy, and surgical arthroscopy. Videos and images were blindly reviewed postoperatively. Analysis included sensitivity, specificity, positive predictive value (PPV), negative predictive value, Cohen's kappa agreement coefficient, and the McNemar test. RESULTS: Needle arthroscopy had similar accuracy to MRI in diagnosing intra-articular shoulder pathologies when both were compared with the gold standard of diagnostic arthroscopy. It had high specificities and PPV for certain rotator cuff tears, biceps pathology, and anterior labral tears. When compared with the gold standard, specificity of needle arthroscopy for diagnosing rotator cuff tear and cartilage lesions was 1.00 and 0.97 and 0.72 and 0.86 for MRIs, respectively. Sensitivity of needle arthroscopy for rotator cuff and cartilage lesions was 0.89 and 0.74, respectively, lower than MRI. For most intra-articular pathologies, needle arthroscopy was at least equally accurate to MRI at diagnosing intra-articular shoulder pathologies, with similar or high kappa statistics when correlated with surgical arthroscopic findings. CONCLUSIONS: Needle arthroscopy is a promising diagnostic modality for intra-articular shoulder pathologies. It had comparable accuracy with MRI for diagnosing articular cartilage, labrum, rotator cuff, and biceps pathology. Across all pathologies, needle arthroscopy had better ability to "rule in" a diagnosis (high specificities and PPV), but slightly worse ability to "rule out" a diagnosis (lower sensitivities and negative predictive value) compared with MRI. LEVEL OF EVIDENCE: Level II, Development of diagnostic criteria on consecutive patients (with universally applied reference "gold" standard).
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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 | 0.019 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".