Utilization of the Ottawa Ankle Rules by Nurses in a Pediatric Emergency Department
Bibliographic record
Abstract
OBJECTIVES: To determine the ability of pediatric emergency department (ED) nurses to accurately apply the Ottawa Ankle Rules (OAR) and to evaluate whether the rate of negative ankle radiographs can be reduced by incorporating the OAR into an existing collaborative practice protocol (CPP). METHODS: The authors' ED currently uses a CPP in which patients with ankle pain, swelling, deformity, or decreased range of motion on primary nursing assessment undergo radiography prior to physician evaluation. A cross-sectional study was conducted between June and November 2000. Patients aged 5-19 years with an ankle injury who met at least one of the CPP criteria were eligible for enrollment. The OAR were applied by the primary nurse after initial assessment. Ankle radiographs were ordered for all enrolled patients. The interobserver variability between nurses was evaluated on a random sample. RESULTS: One hundred ninety subjects were enrolled in the study. The OAR were correctly interpreted by nurses in 98.4% of subjects. Agreement on the interobserver reliability sample was 100%. Of the 185 subjects, 31 (16.8%) had positive radiographs. Positive OAR results were noted in 30 of 31 subjects with positive radiographs. The sensitivity of the OAR was 97% (95% CI = 0.82 to 0.99) with a specificity of 25% (95% CI = 0.18 to 032). Use of the OAR would have reduced the radiography rate by 21%. CONCLUSIONS: Trained nurses can accurately apply and interpret the OAR. The incorporation of the OAR into the nursing assessment of children with acute ankle injuries may reduce the number of radiographs ordered.
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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 | 0.014 | 0.080 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".