Accuracy of Ottawa ankle rules to exclude fractures of the ankle and mid-foot: systematic review
Bibliographic record
Abstract
Abstract Objective: To summarise the evidence on accuracy of the Ottawa ankle rules, a decision aid for excluding fractures of the ankle and mid-foot. Design: Systematic review. Data sources: Electronic databases, reference lists of included studies, and experts. Review methods: Data were extracted on the study population, the type of Ottawa ankle rules used, and methods. Sensitivities, but not specificities, were pooled using the bootstrap after inspection of the receiver operating characteristics plot. Negative likelihood ratios were pooled for several subgroups, correcting for four main methodological threats to validity. Results: 32 studies met the inclusion criteria and 27 studies reporting on 15 581 patients were used for meta-analysis. The pooled negative likelihood ratios for the ankle and mid-foot were 0.08 (95% confidence interval 0.03 to 0.18) and 0.08 (0.03 to 0.20), respectively. The pooled negative likelihood ratio for both regions in children was 0.07 (0.03 to 0.18). Applying these ratios to a 15% prevalence of fracture gave a less than 1.4% probability of actual fracture in these subgroups. Conclusion: Evidence supports the Ottawa ankle rules as an accurate instrument for excluding fractures of the ankle and mid-foot. The instrument has a sensitivity of almost 100% and a modest specificity, and its use should reduce the number of unnecessary radiographs by 30-40%. What is already known on this topic Although most patients with ankle sprains who present to emergency departments undergo radiography, less than 15% have a fracture The Ottawa ankle rules is a clinical decision aid designed to avoid unnecessary radiography What this paper adds The Ottawa ankle rules is highly accurate at excluding ankle fractures after sprain injury
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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 | 0.058 | 0.261 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.021 |
| Bibliometrics | 0.013 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".