Triage Nurse Application of the Ottawa Knee Rule
Bibliographic record
Abstract
OBJECTIVE: To determine interobserver agreement between triage registered nurses (RNs) and emergency physicians (EPs) regarding indication for knee radiographs by applying the Ottawa knee rule (OKR) and individual components of the rule. METHODS: This was a prospective, observational study in a suburban, teaching emergency department. The study enrolled a convenience sample of patients aged >17 years with traumatic knee injuries less than one week old. Patients with prior knee surgery or distracting conditions were excluded. Before study initiation, the RNs and EPs were in-serviced in the OKR. Nurses and EPs independently examined each patient for OKR criteria, blinded to the other's assessment. Knee radiographs were ordered at the discretion of the EP and were interpreted by board-certified radiologists. All patients received follow-up with a structured telephone interview to identify any undetected fractures. Kappa was calculated for each component and the overall application of the OKR to assess interobserver agreement. RESULTS: Ninety-six patients were enrolled. The mean age was 39.6 +/- 18.7 years; 50% were male. Eight patients (8%) had knee fractures. Interobserver agreements between the RNs and EPs for individual components of the OKR were: age > or =55 years (kappa = 0.97); inability to weight bear (kappa = 0.51); inability to bend knee to 90 degrees (kappa = 0.52); fibular head tenderness (kappa = 0.45); and isolated patellar tenderness (kappa = 0.40). The EPs and RNs agreed with OKR criteria for x-ray 71% of the time (kappa = 0.41). CONCLUSIONS: The only criterion that resulted in almost perfect agreement between the RNs and EPs was patient age; agreement for the other four criteria and the overall decision to order x-rays was moderate.
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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 | 0.005 | 0.043 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".