Natural history of minimal aortic injury following blunt thoracic aortic trauma
Bibliographic record
Abstract
BACKGROUND: Endovascular repair of blunt traumatic thoracic aortic injuries (BTAI) is common at most trauma centres, with excellent results. However, little is known regarding which injuries do not require intervention. We reviewed the natural history of untreated patients with minimal aortic injury (MAI) at our centre. METHODS: We conducted a retrospective database review to identify all patients with a BTAI between October 2008 and March 2010. The cohort comprised patients initially untreated because of the lesser degree of injury of an MAI. We reviewed initial and follow-up computed tomography (CT) scans and clinical information. RESULTS: We identified 69 patients with a BTAI during the study period; 10 were initially untreated and were included in this study. Degree of injury included intimal flaps (n = 7, 70%), pseudoaneurysms with minimal hematoma (n = 2, 20%) and circumferential intimal tear (n = 1, 10%). Six (60%) patients were male, and the median age was 40 years. Duration of clinical follow-up ranged from 1 month to 6 years (median 2 mo) after discharge, whereas CT radiologic follow-up ranged from 1 week to 6 years (median 6 wk). Seven (70%) patients had complete resolution or stabilization of their MAI, 1 (10%) with circumferential intimal tear showed extension of the injury at 8 weeks postinjury and underwent successful repair, and 2 (20%) were lost to follow-up. CONCLUSION: There appears to be a subset of patients with BTAI who require no surgical intervention. This includes those with limited intimal flaps, which often resolve. Radiologic surveillance is mandatory to ensure MAI resolution and identify any progression that might prompt repair.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".