Clinical Usefulness of the Ottawa Ankle Rules for Detecting Fractures of the Ankle and Midfoot
Bibliographic record
Abstract
Abstract Reference: Bachmann LM, Kolb E, Koller MT, Steurer J, ter Riet G. Accuracy of Ottawa Ankle Rules to exclude fractures of the ankle and mid-foot: systematic review. BMJ. 2003;326(7386):417–423. Clinical Question: What is the evidence for the accuracy of the Ottawa Ankle Rules as a decision aid for excluding fractures of the ankle and midfoot? Data Sources: Studies were identified by searching MEDLINE and PreMEDLINE (Ovid version: 1990 to present), EMBASE (Datastar version: 1990–2002), CINAHL (Winspires version: 1990–2002), the Cochrane Library (2002, issue 2), and the Science Citation Index database (Web of Science by Institute for Science Information). Reference lists of all included studies were also searched, and experts and authors in the specialty were contacted. The search had no language restrictions. Study Selection: Minimal inclusion criteria consisted of (1) study assessment of the Ottawa Ankle Rules and (2) sufficient information to construct a 2 × 2 contingency table specifying the false-positive and false-negative rates. Data Extraction: Studies were selected in a 2-stage process. First, all abstracts and titles found by the electronic searches were independently scrutinized by the same 2 authors. Second, copies of all eligible papers were obtained. A checklist was used to ensure that all inclusion criteria were met. Disagreements related to the eligibility of studies were resolved by consensus. Both authors extracted data from each included study independently. Methods of data collection, patient selection, blinding and prevention of verification bias, and description of the instrument and reference standard were assessed. Sensitivities (using the bootstrap method), specificities, negative likelihood ratios (using a random-effects model), and their standard errors were calculated. Special interest was paid to the pooled sensitivities and negative likelihood ratios because of the calibration of the Ottawa Ankle Rules toward a high sensitivity. Exclusion criteria for the pooled analysis were (1) studies that used a nonprospective data collection, (2) unknown radiologist blinding (verification bias), (3) studies assessing the performance of other specialists (nonphysicians) using the rules, and (4) studies that looked at modifications to the rules. Main Results: The search yielded 1085 studies, and the authors obtained complete articles for 116 of the studies. The reference lists from these studies provided an additional 15 studies. Only 32 of the studies met the inclusion criteria and were used for the review; 5 of these met the exclusion criteria. For included studies, the total population was 15 581 (range = 18–1032), and average age ranged from 11 to 31.1 years in those studies that reported age. The 27 studies analyzed (pooled) consisted of 12 studies of ankle assessment, 8 studies of midfoot assessment, 10 studies of both ankle and midfoot assessment, and 6 studies of ankle or midfoot assessment in children (not all studies assessed all regions). Pooled sensitivities, specificities, and negative likelihood ratios for the ankle, midfoot, and combined ankle and midfoot are presented in the Table. Based on a 15% prevalence of actual fracture in patients presenting acutely after ankle or foot trauma, less than a 1.4% probability of fracture existed. Because limited analysis was conducted on the data from the children, we elected to not include this cohort in our review. Conclusions: Evidence supports the use of the Ottawa Ankle Rules as an aid in ruling out fractures of the ankle and midfoot. The rules have a high sensitivity (almost 100%) and modest specificity. Use of the Ottawa Ankle Rules holds promise for saving time and reducing both costs and radiographic exposure without sacrificing diagnostic accuracy in ankle and midfoot fractures.
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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 | 0.340 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.031 | 0.016 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".