The usefulness of MRI and arthroscopy in the diagnosis and treatment of soft-tissue injuries associated with split-depression fractures of the lateral tibial condyle
Bibliographic record
Abstract
The role of arthroscopy in the treatment of soft-tissue injuries associated with proximal tibial fractures remains debatable. Our hypothesis was that MRI over-diagnoses clinically relevant associated soft-tissue injuries. This prospective study involved 50 consecutive patients who underwent surgical treatment for a split-depression fracture of the lateral tibial condyle (AO/OTA type B3.1). The mean age of patients was 50 years (23 to 86) and 27 (54%) were female. All patients had MRI and arthroscopy. Arthroscopy identified 12 tears of the lateral meniscus, including eight bucket-handle tears that were sutured and four that were resected, as well as six tears of the medial meniscus, of which five were resected. Lateral meniscal injuries were diagnosed on MRI in four of 12 patients, yielding an overall sensitivity of 33% (95% confidence interval (CI) 11 to 65). Specificity was 76% (95% CI 59 to 88), with nine tears diagnosed among 38 menisci that did not contain a tear. MRI identified medial meniscal injuries in four of six patients, yielding an overall sensitivity of 67% (95% CI 24 to 94). Specificity was 66% (95% CI 50 to 79), with 15 tears diagnosed in 44 menisci that did not contain tears. MRI appears to offer only a marginal benefit as the specificity and sensitivity for diagnosing meniscal injuries are poor in patients with a fracture. There were fewer arthroscopically-confirmed associated lesions than reported previously in MRI 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 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".