The Efficacy of Magnetic Resonance Imaging in Acute Knee Injuries
Bibliographic record
Abstract
OBJECTIVE: To evaluate the clinical efficacy of magnetic resonance imaging (MRI) of the knee in acute injuries with indeterminate clinical findings, using arthroscopy as a gold standard. DESIGN: A prospective double-blind study was performed. All patients underwent MRI on a 1.5 T magnet using dual spin echo pulse sequences. This was followed by arthroscopy. SETTING: Tertiary care referral center. PATIENTS: Twenty-three patients with an average age of 26 years satisfied the study criteria. Patients had to have been seen by one of two orthopaedic surgeons within 6 weeks of sudden trauma to the knee complicated by a hemarthrosis, clinical assessment of which was equivocal. RESULTS: The respective sensitivity and specificity for MRI of the knee were 90% (18/20) and 67% (2/3) for detecting any anterior cruciate ligament injury, 50% (1/2) and 86% (18/21) for detecting medial meniscal tears, and 88% (7/8) and 73% (11/15) for detecting lateral meniscal tears. MRI also identified injuries that could not be assessed on arthroscopy, including 14 bone bruises, five posterior cruciate ligament tears, nine medial collateral ligament tears, and one lateral collateral ligament tear. The detection of composite injury requiring surgical intervention yielded a sensitivity of 100% (16/16) and a specificity of 71% (5/7). Prospective use of MRI evaluation of the knee could have prevented 22% (5/23) of diagnostic arthroscopic procedures. CONCLUSION: Equivocal clinical findings in patients with acute knee injury should lead to use of MRI in an appropriate clinical setting. To our knowledge a prospective study of the efficacy of MRI of the knee in this patient population has not been reported. In the presence of such inclusion criteria, the results of our study support the use of early MRI to guide further surgical management.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".