Evaluating fracture risk in acute ankle sprains: Any news since the Ottawa Ankle Rules? A systematic review
Bibliographic record
Abstract
BACKGROUND: Ankle sprain is frequently encountered, both in primary care and in emergency departments. Since 1992, the Ottawa ankle rules (OAR) can assist clinicians in determining whether an X-ray should be performed to exclude a fracture. Several guidelines recommend the use of OAR based on a systematic review from 2003. Ten years later, one can wonder if this recommendation should be changed. OBJECTIVE: To review systematically the current evidence on the most accurate method to assess the fracture risk after an ankle sprain in adults. METHODS: A methodical search for systematic reviews, meta-analyses and primary studies was carried out in Medline, Cochrane Database of systematic reviews, Embase, Pedro, CINAHL, Medion and specific guideline search engines. At least two independent researchers performed selection, quality appraisal (with validated checklists) and data extraction. RESULTS: One systematic review and 21 primary studies were selected. Sensitivity and specificity of the OAR range from 92-100% and from 16-51%, respectively. To improve the OAR specificity, other tools are proposed such as the Bernese ankle rules. Vibrating tuning fork test and ultrasound could be useful in patient with OAR positive to decrease the need for radiographs. No evidence was found in favour of the use of magnetic resonance imaging (MRI) or computed tomography (CT) in the acute phase of ankle sprain. CONCLUSION: The findings confirm the value of the OAR at ruling out fractures after an ankle sprain and propose other or additional tools to decrease the need for X-rays.
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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 | 0.029 | 0.114 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.009 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".