P.064 Physician Approaches to Imaging and Revascularization for Acutely Symptomatic Carotid Stenosis: Insights from the Hot Carotid Qualitative Study
Bibliographic record
Abstract
Background: Evidence informing the choice between endarterectomy and stenting for acutely symptomatic carotid stenosis (“hot carotid”) is dated, and uncertainties remain regarding the optimal imaging modality. We sought to explore the thoughts of stroke physicians regarding the perioperative management of patients with acute symptomatic carotid stenosis. Methods: We conducted semi-structured interviews regarding “hot carotid” management with purposive sampling of 20 stroke physicians from 14 centres in North America, Europe, Asia, and Australia. We identified key themes using conventional qualitative content analysis. Results: Timely imaging availability, breadth of information gained, and surgeon/interventionalist preference emerged as important themes informing the choice of imaging modality. Multidisciplinary decision making, operating room/angiography suite availability, and implications of patient age and infarct size were important themes related to the choice of revascularization. Areas of uncertainty included utility of carotid plaque imaging, timing of revascularization, and the role of intervention with borderline stenosis or intraluminal thrombus. Conclusions: Our qualitative analysis revealed themes that were important to stroke experts. Teams designing international trials will have to accommodate identified variations in practice patterns and take into consideration areas of uncertainty, such as timing of revascularization, imaging of carotid plaque and non-stenotic features of carotid disease (intraluminal thrombus, plaque morphology).
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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 | 0.023 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".