Computed tomography evaluation of traumatic rupture of the thoracic aorta: an outcome study.
Bibliographic record
Abstract
OBJECTIVE: [corrected] To assess the long-term outcome of blunt trauma patients with suspected thoracic aortic or great vessel injury that was evaluated with contrast-enhanced chest computed tomography (CT). METHODS: We studied the outcome of 278 consecutive patients who received contrast-enhanced CT for blunt chest trauma with computerized searches of the regional trauma database, hospital medical records, universal government medical coverage plan billing records, and regional vital statistics databases. Data retrieved included patient demographics, mechanism of injury, status of the aorta and proximal great vessels at contrast-enhanced CT, hospital discharge diagnoses, and outpatient procedural billings with specific attention to aortic or great vessel injury. Median follow-up was 615 days following the traumatic event. RESULTS: Six subjects demonstrated direct signs of aortic or proximal great vessel injury on contrast-enhanced chest CT, as follows: aortic pseudoaneurysm and intimal flap (n = 4), carotid artery dissection (n = 1), and aortic dissection (n = 1). All were surgically treated, except the patient with aortic dissection, who was treated medically. In the other subjects, contrast-enhanced CT was negative (n = 230) or showed isolated mediastinal hematoma (n = 42). The computerized searches of the medical databases showed that none of these 272 subjects had procedures for, or died from, aortic or great vessel injury during the follow-up period. CONCLUSION: Computerized searches of medical databases found no evidence of missed thoracic aortic or proximal great vessel injury in blunt trauma patients who were evaluated with contrast-enhanced chest CT.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".