Validation of the Ottawa Ankle Rule in Blunt Ankle and Midfoot Injuries in a Trauma Care Centre in Nigeria
Bibliographic record
Abstract
Objectives: Ankle and midfoot injuries are common presentations in every emergency department. The Ottawa Ankle Rule was developed to reduce the need for unnecessary radiography. This study aimed to validate this rule in a population. Materials and Methods: This study recruited 110 patients in a single-trauma care centre presenting with closed ankle and midfoot injuries. All patients were examined using the Ottawa Ankle Rule by orthopaedic surgeons and findings were recorded before radiographs were obtained. The radiographs were interpreted by a consultant radiologist blinded by the clinical examination findings. This was the standard against which the Ottawa Ankle Rule was tested. Results: The sensitivity of the Ottawa Ankle Rule protocol in ankle and midfoot injuries was 100% and 95%, respectively. The specificity was 37.2% for ankle injuries and 54.8% for midfoot injuries. The negative predictive value of the rule was 100% and 95.1% for ankle and midfoot injuries, respectively. Application of this rule would have led to a 31% reduction in radiography amongst patients in this study. Conclusion: The Ottawa Ankle Rule is a valid decision-making tool for patients with closed ankle and midfoot injuries. It has a high sensitivity for detecting fractures with moderate specificity. Application of the rule can result in a significant reduction of; treatment costs, waiting times at the emergency department, and unnecessary radiation exposure to patients.
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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 | 0.008 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.001 | 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".