Endovascular Treatment for Cerebral Venous Thrombosis: Applying Lessons Learned from Clinical Trials of Endovascular Treatment in Acute Arterial Ischemic Stroke
Bibliographic record
Abstract
BACKGROUND: Cerebral venous thrombosis (CVT) is a rare but severely disabling form of stroke. Acute treatment mainly consists of medical management, since there is no robust evidence suggesting the benefit of endovascular treatment for CVT. Given the relative lack of data to guide acute treatment decision-making, CVT treatment decisions are mostly made on a case-by-case basis. In some ways, the current status quo of endovascular treatment for CVT resembles the state of endovascular treatment for acute ischemic stroke before the wave of major positive large vessel occlusion endovascular treatment trials in 2015. SUMMARY: The current state of evidence with regard to endovascular CVT treatment is summarized, parallels to acute ischemic stroke are drawn, and it is discussed how the lessons learned from the evolution of acute ischemic stroke endovascular treatment (EVT) trials could be applied to designing a trial of endovascular treatment for CVT. The review ends by outlining possible scenarios for the future of endovascular CVT treatment. KEY MESSAGES: CVT is a serious disease, affecting young patients and their families, and harbors a considerable social and economic burden. Working toward high-level evidence for the best possible treatment strategy and exploring a possible role for EVT to improve outcomes in CVT needs to remain a high priority in stroke research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.027 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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; both teacher heads agree on what is shown here.
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".