Early vascular imaging and key system strategies expedite carotid revascularization after transient ischemic attack and stroke
Bibliographic record
Abstract
BACKGROUND: International guidelines recommend carotid revascularization within 14 days for patients with a symptomatic transient ischemic attack (TIA) or stroke event. However, significant delays in care persist, with only 9% of outpatients and 36% of inpatients in Ontario meeting this target. The study objective was to explore the influence of health system factors on carotid revascularization timelines. METHODS: We conducted a retrospective chart review of all symptomatic TIA/stroke patients undergoing carotid endarterectomy or stenting at The Ottawa Hospital (2015-2016). The primary outcome was time from TIA/stroke to carotid revascularization. Health system variables of interest included location and timing of patient presentation, timelines to vascular imaging, and same-day collaboration between key services such as emergency, neurology, and surgery. Descriptive statistics and univariate analysis were used to determine statistically significant differences between groups. RESULTS: A total of 228 records met the inclusion criteria. The median time from TIA/stroke to carotid revascularization was 10 days, with 58% of patients meeting the 14-day guideline. Prompt patient presentation to emergency demonstrated significantly shorter timelines to surgery (7 days; P < .001). Early vascular imaging was strongly correlated with early revascularization (4-5 days; P < .001). In addition, collaboration from two or more care services enhanced timelines to surgery ranging from 2.0 to 6.5 days (P < .001-.008). CONCLUSIONS: Early/emergency response to stroke symptoms was pivotal in achieving best practice recommendations for rapid carotid revascularization, emphasizing the need for ongoing public awareness. Emergency and ambulatory strategies to facilitate urgent vascular imaging, as well as mechanisms for same-day communication between teams require optimization to promote early revascularization.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".