An Update in Imaging of Blunt Vascular Neck Injury
Bibliographic record
Abstract
Traumatic injuries of the cervical carotid and vertebral arteries, collectively referred to as blunt cerebrovascular injury (BCVI), can result in significant patient morbidity and mortality, with one of the most feared outcomes being cerebrovascular ischemia. Systematic imaging-guided screening for BCVI aims for early detection to guide timely management. In particular, accurate detection of the severity and grade of BCVI is paramount in guiding initial management. Furthermore, follow-up imaging is required to decide the duration of antithrombotic therapy. In this article, classification of the grades of BCVI and associated imaging findings will be outlined and diagnostic pitfalls and mimickers that can confound diagnosis will be described. In addition, updates to existing screening guidelines and recent efforts of criteria modification to improve detection of BCVI cases will be reviewed. The advent of postprocessing tools applied to conventional computed tomography (CT) angiograms and new diagnostic tools in dual energy CT for improved detection will also be discussed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".