THE EVALUATION OF THE OTTAWA ANKLE CRITERIA IN PATIENTS REFERING TO THE EMERGENCY DEPARTMENT FOR ANKLE STRAIGHTENING
Bibliographic record
Abstract
Aim: The aim of our study was to investigate the effectiveness of Ottawa Ankle Rules (OAR) in turkish society. Method: 208 patients with ankle injuries following a trauma were included to our study in October 17 2016 to January 17 2017.All patients were referred for standard radiograhy of ankle and they were evaluated regarding the OAR. Age, gender, mechanism of the trauma, the reason of injury were asked, the patients consultated to orthopedics and the ones needed to ateles were recorded. Statistics were analysed according to SPSS 16th version. Results: It is found that 2 of 208 patients had no endication of standard graphy according to OAR and there were no fractures in these patients. According to OAR 206 patients had endication for radiography and in this group 33 patients had fractures. The sensivity of OAR is 100% and specificity of OAR is 27% for turkish society. It could prevent 25% of the unnecessary radiographies. The severity of the injuries increased by patients’ age got older. Especially it should not be forgotten that in elderly patients and fat patients even little injuries could cause fractures, so physicians should pay more attention to these patients. Conclusion: Ankle injuries following a trauma should be evaluated regarding the OAR to gain time in the emergency department and patients will take less radiation and also it could be more cost effective.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".