Reducing the global burden of cerebral venous thrombosis: An international research agenda
Bibliographic record
Abstract
BACKGROUND: Due to the rarity of cerebral venous thrombosis (CVT), performing high-quality scientific research in this field is challenging. Providing answers to unresolved research questions will improve prevention, diagnosis, and treatment, and ultimately translate to a better outcome of patients with CVT. We present an international research agenda, in which the most important research questions in the field of CVT are prioritized. AIMS: This research agenda has three distinct goals: (1) to provide inspiration and focus to research on CVT for the coming years, (2) to reinforce international collaboration, and (3) to facilitate the acquisition of research funding. SUMMARY OF REVIEW: This international research agenda is the result of a research summit organized by the International Cerebral Venous Thrombosis Consortium in Amsterdam, the Netherlands, in June 2023. The summit brought together 45 participants from 15 countries including clinical researchers from various disciplines, patients who previously suffered from CVT, and delegates from industry and non-profit funding organizations. The research agenda is categorized into six pre-specified themes: (1) epidemiology and clinical features, (2) life after CVT, (3) neuroimaging and diagnosis, (4) pathophysiology, (5) medical treatment, and (6) endovascular treatment. For each theme, we present two to four research questions, followed by a brief substantiation per question. The research questions were prioritized by the participants of the summit through consensus discussion. CONCLUSIONS: This international research agenda provides an overview of the most burning research questions on CVT. Answering these questions will advance our understanding and management of CVT, which will ultimately lead to improved outcomes for CVT patients worldwide.
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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 | 0.031 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.015 | 0.013 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".