Alternative Imaging Modalities to DSA in the Acute Phase of Unruptured Vertebral Artery Dissection
Bibliographic record
Abstract
Minor neck movements are a known cause of vertebral artery dissection even without any evidence of trauma. However, there are limited reports of unilateral vertebral artery dissection in a trauma patient evolving to a fatal posterior fossa infarction within one day, in the absence of any neurological deficit or a focal lesion on brain CT. We report such a case and comment on the overall efficiency of diagnostic alternatives to classic angiography that can be used in the acute phase of unruptured vertebral artery dissection. We present a case of a healthy 55 year old trauma patient with initial good neurological presentation and normal non-infused brain CT who deteriorated 16 hours following injury and deceased the following day due to a massive posterior fossa infarction and extended cerebral edema caused by vertebral artery dissection. We conclude that any trauma patient with a persistent, even mild occipital headache or neck pain can be a candidate for vertebral artery dissection. Such pathology requires both a high index of suspicion and the proper imaging modality. Vertebral artery dissection can be efficiently visualized by multisection CT angiography which is fast, accurate and non-invasive. This modality can be an alternative to classic angiography especially in emergency settings where it may not be easily available. doi:10.4021/jmc696w
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".