Implementation of the Ottawa ankle rules by general practitioners in an emergency department of a Turkish district hospital
Bibliographic record
Abstract
BACKGROUND: The present objective was to assess implementation of the Ottawa ankle rules (OAR) as a method of fracture prediction in the emergency department (ED) of a Turkish state hospital. METHODS: Patients who presented to the ED of our hospital with acute ankle injury were evaluated. All were examined by a general practitioner, after which a series of ankle and foot x-rays (anteroposterior and lateral) were performed. Radiography was examined by a radiologist and an orthopedic surgeon, both of whom were blinded to OAR results. Radiographic results were compared to results of OAR implementation. Sensitivity and specificity of the OAR in the diagnosis of fracture was calculated. RESULTS: A total of 251 (61.97%) patients were diagnosed as positive (+) for fracture after OAR implementation, 154 (38.02%) as negative (-). Clinically significant fracture was detected in 62 (15.3%) patients. A total of 61 (98.4%) patients with significant fracture were OAR (+); 1 (1.6%) was OAR (-). However, 190 (55.4%) patients without fracture were OAR (+); 153 (44.6%) were OAR (-) (p<0.001). Sensitivity, specificity, and positive and negative predictive values of OAR implementation in the prediction of fracture were 98.39%, 44.61%, 24.30%, and 99.35%, respectively. Area under the curve (AUC) was 0.71. According to these results, it was determined that use of radiography could be reduced by 38.02% if the OAR were implemented. CONCLUSION: The OAR are a highly sensitive means of screening of patients with acute ankle and mid-foot injuries. Application of the OAR by well-trained general practitioners can lead to significant reduction in the number of x-rays performed, thereby reducing cost of treatment and radiation exposure, in addition to saving time for patients and staff.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".