Cervical Arterial Dissection
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Cervical arterial dissection is a major cause of stroke in young adults, yet despite standard treatment with anticoagulants or antiplatelet drugs, its management remains uncertain. The goal of this study was to assess the natural history of the disorder and to decide on the feasibility of a therapeutic trial. METHODS: Collaborating members of the Canadian Stroke Consortium prospectively enrolled consecutively referred patients with angiographically proven acute vertebral or carotid arterial dissection. Data recorded included clinical and radiological details, recurrence of ischemic cerebral events, and medical or surgical treatment. RESULTS: Of 116 patients, 67 had vertebral and 49 had carotid dissections, with no difference in age or sex. In 68 (59%), trauma occurred at the time of dissection. During the course of a 1-year follow-up, at least 17 patients (15%) had recurrent transient ischemic attacks, stroke, or death, mainly in the weeks immediately after the dissection. In 105 patients with complete follow-up, the event rate in those treated with anticoagulants was 8.3% and in those treated with aspirin was 12.4%, a nonsignificant difference of 4.1%. Using these data, we calculate that for a 2-arm trial (aspirin versus anticoagulants) with 80% power and 5% significance, 913 patients are needed in each group. CONCLUSIONS: From our data indicating an initial relatively high recurrence rate, a multicenter trial of anticoagulants versus aspirin involving a total of 2000 patients is feasible.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.007 | 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".