Accuracy of Ottawa Ankle Rules to Exclude Fractures of the Ankle and Midfoot in Children: A Meta‐analysis
Bibliographic record
Abstract
OBJECTIVES: The objectives were to conduct a systematic review to determine the diagnostic accuracy of the Ottawa Ankle Rules (OAR) to exclude ankle and midfoot fractures in children and the extent to which x-ray use could be reduced without missing significant fractures. METHODS: The authors conducted comprehensive searches of electronic databases and gray literature sources. Independent reviewers applied standard inclusion and exclusion criteria. The criterion standard diagnostic test was an ankle and/or foot x-ray or proxy measure to ensure no missed fractures. Standard 2 x 2 tables were constructed. Sensitivities and specificities were pooled using an approximation of the inverse variance; 95% confidence intervals (95% CIs) were calculated using the exact method. Likelihood ratios (LR +/-) and diagnostic odds ratios were combined under DerSimonian and Laird random effects model. RESULTS: A pooled analysis of 12 studies (N = 3,130) identified 671 fractures (prevalence = 21.4%). Ten studies reported Salter-Harris Type I (SH-I) fractures. The pooled sensitivity was 98.5% (95% CI = 97.3 to 99.2), suggesting that the OAR can be used to rule out a fracture. Four of 10 missed fractures were characterized: 1 SH-I, 1 SH-IV, and 2 "insignificant fractures" (either SH-I or avulsion fractures <3 mm). The pooled estimate for rate of x-ray reduction was 24.8% (95% CI = 23.3% to 26.3%; range = 5% to 44%). CONCLUSIONS: The OAR appear to be a reliable tool to exclude fractures in children greater than 5 years of age presenting with ankle and midfoot injuries. Employing the OAR would significantly decrease x-ray use with a low likelihood of missing a fracture.
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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 | 0.036 | 0.094 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.051 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".