Ottawa Ankle Rules and their association with ligamentous or chondral injuries of the ankle: a prospective observational study
Bibliographic record
Abstract
Objective: Evaluate the association between the Ottawa Ankle Rules (OAR) and the presence of ligamentous and chondral injuries identified on magnetic resonance imaging (MRI). Methods: A prospective observational study was conducted in 48 patients who underwent clinical evaluation using the OAR with subsequent MRI assessment. Variables analyzed included patient age, gender, laterality, and presence of ligamentous or chondral injuries. Statistical analyses were performed using the Shapiro-Wilk test for normality, Student’s t-test for age comparisons, and Pearson’s chi-square test to assess associations between categorical variables. Results: Mean age of patients was 41.06 years, ranging from 15 years to 82 years. Groups with positive and negative OAR results were homogeneous regarding age (p = 0.29), gender (p = 0.42), and laterality (p = 0.09). No significant association was found between a positive OAR and the presence of ligamentous injuries (p = 0.42) or chondral injuries (p = 0.83) on MRI. Conclusion: The OAR were not associated with ligamentous or chondral injuries identified on MRI, suggesting their limitations in predicting these specific findings. Further studies are needed to develop a more accurate predictive model incorporating clinical and imaging parameters. Level of Evidence IV; Prospective Observational; Case Series
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".