[X-ray requests for minor limb injuries. A systematic review].
Bibliographic record
Abstract
X-ray requests for minor limb trauma: a systematic review. INTRODUCTION: Overcrowding in Emergency Department (ED) leads to an increased waiting time causing dissatisfaction both in patients and staff, in addition to possible negative events. AIM: To assess if the request of x-rays by triage nurses, for isolated injuries, during the waiting time before the physician assessment, might improve the flow of ED patient, affecting the lenght of stay (LOS) and the waiting time in the department. Nurses' satisfaction in addition to the accuracy of the requested x-rays was also assessed. METHODS: A systematic review was conducted according to the PRISMA method, questioning PUBMED and CINAHL databases, selecting full text articles from the year 1995 and considering only adult population. RESULTS: 14 studies were selected: 7 RCT, 5 observational studies, 1 pilot study and 1 quasi-experimental study. The request of x-rays by the triage nurses significantly improved the waiting and staying time in the ED together with the patients and staff's satisfaction. CONCLUSIONS: Anticipating the x-rays requests during triage can be a solution for reducing waiting and staying time in the ED. In addition, it impacts also on patients and nurses' satisfaction. The accuracy of x-rays is strictly linked to Nurses' education and the use of validated tools like Ottawa Ankle Rules, which had good feedback from the nursing staff.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".