Bibliographic record
Abstract
Dissection of the extracranial carotid and vertebral arteries is increasingly recognized as a cause of transient ischemic attacks and stroke. The annual incidence of spontaneous carotid artery dissection is 2.5 to 3 per 100,000, while the annual incidence of spontaneous vertebral artery dissection is 1 to 1.5 per 100,000. Traumatic dissection occurs in approximately 1% of all patients with blunt injury mechanisms, and is frequently initially unrecognized. Overall, dissections are estimated to account for only 2% of all ischemic strokes, but they are an important factor in the young, and account for approximately 20% of strokes in patients less than 45 years of age. Arterial dissection can cause ischemic stroke either by thromboemboli forming at the site of injury or as a result of hemodynamic insufficiency due to severe stenosis or occlusion. Available evidence strongly favors embolism as the most common cause. Both anticoagulation and antiplatelet agents have been advocated as treatment methods, but there is limited evidence on which to base these recommendations. A Cochrane review on the topic of antithrombotic drugs for carotid dissection did not identify any randomized trials, and did not find that anticoagulants were superior to antiplatelet agents for the primary outcomes of death and disability. Healing of arterial dissections occurs within three to six months, with resolution of stenosis seen in 90%, and recanalization of occlusions in as many as 50%. Dissecting aneurysms resolve on follow-up imaging in 5-40%,decrease in size in 15-30%, and remain unchanged in 50-65%. Resolution is more common in vertebral dissections than in carotid dissections. Aneurysm enlargement occurs rarely. The uncommon patient presenting with acute hemodynamic insufficiency should be managed with measures to increase cerebral blood flow, and in this setting emergency stent placement to restore cerebral perfusion may be considered, provided that irreversible infarction has not already occurred.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".