FAST VAN Large Vessel Occlusion Stroke Screen
Bibliographic record
Abstract
Saskatchewan has 8 primary stroke centers (PSC) and one comprehensive stroke center (CSC) to serve a vast geographical location. The province has an urgent need to develop a system of care that supports appropriate transfer of large vessel occlusion (LVO) stroke patients to the CSC for mechanical thrombectomy. Making transport decisions based on clinical symptoms is the ultimate goal. There are a variety of LVO field tests being trialed around the world. These tests are intended to direct emergency medical services (EMS) in communicating clinical stroke symptoms and perhaps, lead to bypass protocols when clinically relevant. In close collaboration with EMS and PSCs the Saskatchewan Stroke Expert Panel initiated a provincial LVO field test u2013 FAST VAN. This screening tool incorporates the traditional FAST signs of stroke; face, arm and speech, with three commonly seen cortical symptoms experienced with LVO; visual gaze preference, aphasia and tactile neglect. FAST VAN reflects current expert practice and follows basic clinical principles. It allows for rapid assessment with minimal training required and is easily integrated with existing protocols. Preliminary retrospective chart reviews have shown that the FAST VAN screen has a sensitivity of 89% and a specificity of 75%. Ongoing data collection on the accuracy of use is being determined by: EMS symptom identification, physician verification and neurovascular imaging confirmation of an LVO.
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 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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.045 | 0.018 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.018 | 0.035 |
| Open science | 0.031 | 0.050 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.101 | 0.096 |
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".