Ultrasound-assisted external fixation: a technique for austere environments
Bibliographic record
Abstract
INTRODUCTION: Ultrasound-assisted external fixation of long bones has the potential to enhance extremity damage control surgery in locations without fluoroscopy, such as forward surgical elements, the intensive care unit, and spacecraft. This pre-clinical study specifically sought to evaluate orthopaedic surgeons' ability to sonographically define fracture patterns and the associated zone of injury in order to improve surgical decision-making and safely insert Schanz pin percutaneously. METHODS: We encased small composite femurs in a cylindrical echogenic gelatin matrix to simulate a human thigh. Three orthopaedic trauma surgeons with no prior ultrasound experience were taught to use sonography to diagnose fractures and assist external fixation. The surgeons were then presented with five specimens in a randomized sequence: three diaphyseal fractures (32-A2, 32-C2 and 32-C3); a distal femur fracture (33-A1.2); and an intact femur, all encased in an opaque black gelatin matrix to blind the participants to the underlying pathology. If they diagnosed a diaphyseal fracture, the surgeons were instructed to insert two Schanz pins proximal and two distal to the fracture, no closer than 40 mm from the fracture edges. RESULTS: Fracture diagnosis and surgical decision-making were correct in all cases. All intact femurs were recognized as such. The need for a knee-spanning external fixator was recognized for all distal femur fractures. The three surgeons performed appropriate ultrasound-assisted pin placement in every case of diaphyseal fracture. The pins adjacent to the fracture site were on average 58 mm (SD ±11 mm) from the edge of the fracture. No pins were inserted in the fracture or in the knee joint. CONCLUSIONS: The current study results suggest that with minimal training, orthopaedic surgeons can use portable ultrasound to diagnose femur fractures, decide the appropriate external fixator configuration, and safely insert Schanz pins outside the zone of injury.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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".