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 carotid endarterectomy and carotid artery stenting for acutely symptomatic carotid stenosis ("hot carotid") is dated and does not factor in contemporary therapies or techniques. The optimal imaging modality is also uncertain. We explored the attitudes of stroke physicians regarding imaging and revascularization of patients with acute symptomatic carotid stenosis. Methods: We used a qualitative descriptive methodology to examine decision-making approaches and opinions of physicians regarding the choice of imaging and revascularization procedures for hot carotids. We conducted semistructured interviews with purposive sampling of 22 stroke physicians from 16 centers in 6 world regions and various specialties: 11 neurologists, 3 geriatricians, 5 interventional neuroradiologists, and 3 neurovascular surgeons. Results: Qualitative analysis revealed several themes regarding clinical decision-making for hot carotids. Whereas CT angiography was favored by most participants, timely imaging availability, breadth of information gained, and surgeon/interventionalist preferences were important themes influencing the choice of imaging modality. Carotid endarterectomy was generally favored over carotid artery stenting, but participants' choice of intervention was influenced by healthcare system factors such as use of multidisciplinary vascular teams and operating room or angiography suite availability, and patient factors like age and infarct size. Areas of uncertainty included choice of imaging modality for borderline stenosis, utility of carotid plaque imaging, timing of revascularization, and the role of intervention with borderline stenosis or intraluminal thrombus. Conclusions: This qualitative study highlights practice patterns common in different centers around the world, such as the general preference for CT angiography imaging and carotid endarterectomy over carotid artery stenting but also identified important differences in availability, selection, and timing of imaging and revascularization options. To gain widespread support, future carotid trials will need to accommodate identified variations in practice patterns and address areas of uncertainty, such as optimal timing of revascularization with modern best medical management and risk-stratification with imaging features other than just degree of stenosis.
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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 | 0.024 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".