Digital Hand-held Sonography Utilised for the Focused Assessment with Sonography for Trauma: A Pilot Study
Bibliographic record
Abstract
OBJECTIVE: To evaluate the accuracy of the focused assessment with sonography for trauma (FAST) exam performed with a digital hand-held ultrasound machine in the emergency evaluation and resuscitation of trauma victims. INTRODUCTION: The FAST exam is a valuable screening tool in the evaluation of abdominal trauma. New digital ultrasound units have recently become available which can be hand-carried by clinicians responding to the earliest phases of trauma care. MATERIALS AND METHODS: Forty-seven victims of blunt trauma and 3 victims of penetrating trauma underwent FAST examinations performed by an attending trauma surgeon. Scans were performed with a Sonosite 180, 2.4-kg machine utilising a 5-2 MHz curved array transducer. The results of the hand-held FAST were compared with formal sonographic examinations performed by radiology department personnel, computed tomographic (CT) studies, operative findings and ultimate hospital course. RESULTS: In victims of blunt trauma, 7 of 8 true fluid collections were detected, and 38 out of 39 cases without the presence of fluid were correctly excluded. There was 1 false positive and 1 false negative determination, resulting in a sensitivity of 86%, specificity of 97%, positive predictive value of 88%, and a negative predictive value of 97%. The overall accuracy was 96% for victims of blunt trauma. The technique expediently detected intra-peritoneal bleeding in 2 victims of lateral penetrating abdominal trauma. Utilised as the initial component of a diagnostic protocol, no inappropriate management strategies were suggested. CONCLUSIONS: Digital hand-held sonography by clinicians can accurately allow the early performance of FAST exams. This exam may accurately and safely extend the physical senses of the examining physician.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| 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".