Bibliographic record
Abstract
P154 Background Cervical arterial dissections are one of the leading causes of stroke in the young. Role of trauma in the pathophysiology of dissection is underestimated, especially since neurological presentation may be delayed and traumatic cases are often judged as “spontaneous”. Role of genetic predisposition is unclear. Methods The Canadian Stroke Consortium is presently conducting a prospective national study of arterial cervical dissections. We are collecting data on the mechanism of dissection (spontaneous or traumatic) and therapeutic strategies. All cases have angiographic confirmation. Results In 94 patients so far (m/f:52/42;mean age 43.2,range 16–87) there were 62 vertebral artery (VA) and 32 carotid artery (CA) dissections. “Violent” trauma (e.g.neck manipulation) caused 20 dissections in VA and 6 in CA group. Trivial trauma (e.g.various head turns, heavy lifting, etc.) included 32 cases in VA and 12 in CA group. The median time between trauma and clinical presentation was 24 hours (minutes-49 days in VA and minutes-25 days in CA group). Fibromuscular dysplasia or Marfan’s syndrome were observed in 14 patients. There were 6 (10%) cases of recurrent episodes in VA group vs. 5(16%) in carotid [12% overall] despite pharmaceutical intervention before discharge. The severity varied from TIAs to devastating strokes. Conclusions The majority of cervical arterial dissections are traumatic. Careful history taking is essential in deciding the mechanism of dissection. Neurological symptoms may occur within months after trauma due to the permanent vascular damage consequent to dissection. Detailed assessment of underlying vascular structural fragility is needed to define patients at risk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".