Abstract TMP14: Population-Based Intracranial Vascular Imaging for Acute Ischemic Stroke is Suboptimal
Bibliographic record
Abstract
Introduction: Endovascular thrombectomy (EVT) is the standard of care for patients with ischemic stroke and large vessel occlusion (LVO). Intracranial vascular imaging is required to determine the presence of an LVO. Although patients can be eligible for EVT up to 24h after last seen normal (LSN), current imaging protocols focus on the first 6h from LSN. We evaluated the use of intracranial vascular imaging in patients with ischemic stroke as a function of time since LSN in Ontario, Canada. Methods: We analyzed data from the Ontario Stroke Registry which performed primary data collection evaluating care and outcomes in 13,828 patients hospitalized with stroke across Ontario in the fiscal year 2019/20. This sampling strategy included 93.3% of all strokes in a province of 14.5 million residents. We used modified Poisson regression models to evaluate the association between time from LSN to first hospital presentation (<6h, 6-12h, 12-24h) and receipt of intracranial vascular imaging with computed tomographic angiography or magnetic resonance angiography. We adjusted for baseline differences and estimated the adjusted relative risk (aRR) of imaging. Results: Data collection is >75% completed and full results will be presented at the ISC. Of 8,482 patients with ischemic stroke, 6,345 (74.8%) presented within 24h of LSN (n=3,811 <6h; n=1,368 6-12h; n=1,166 12-24h). Median age was 76 years (IQR 66-85) and 3,002 (47.3%) were women. Overall, 5,196 (81.9%) patients had intracranial vascular imaging, but compared to those within 6h of LSN (86.8% imaged), patients presenting later were less likely to receive vascular imaging (77.2% for 6-12h, aRR 0.91 95%CI [0.88, 0.94] and 71.4% for 12-24h, aRR 0.85 95%CI [0.82, 0.88]). Of those imaged, 895 (17.2%) had an LVO (18.5% <6h; 16.4% 6-12h, 13.3% 12-24h, p<0.01) and 492 (55.0%) patients with LVO underwent EVT. Conclusions: On a population basis, over 80% of patients with ischemic stroke had intracranial vascular imaging, but gaps in care exist for those presenting in the later time window. Up to one in three patients presenting beyond 6h from LSN did not have vascular imaging. Systems of care must be optimized to support LVO identification and EVT access in later time windows.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".