Carotid Endarterectomy Versus Carotid Artery Stenting: Survey of the Quality, Readability, and Treatment Preference of Carotid Artery Disease Websites
Bibliographic record
Abstract
BACKGROUND: The internet is becoming increasingly more important in the new era of patient self-education. Carotid endarterectomy (CEA) and carotid artery stenting (CAS) are recognized interventions to treat patients with carotid artery stenosis. Using the Google search platform, patients encounter many websites with conflicting information, which are sometimes difficult to understand. This lack of accessibility creates uncertainty or bias toward interventions for carotid artery disease. The quality, readability, and treatment preference of carotid artery disease (CAD) websites have not yet been evaluated. OBJECTIVE: This study aimed to explore the quality, readability, and treatment preference of CAD websites. METHODS: We searched Google Canada for 10 CAD-related keywords. Returned links were assessed for publication date, medical specialty and industry affiliation, presence of randomized controlled trial data, differentiation by symptomatic status, and favored treatment. Website quality and readability were rated by the DISCERN instrument and Gunning Fog Index. RESULTS: We identified 54 unique sites: 18 (33.3%) by medical societies or individual physicians, 11 (20.4%) by government organizations, 9 (16.7%) by laypersons, and 1 (1.9%) that was industry-sponsored. Of these sites, 26 (48.1%) distinguished symptomatic from asymptomatic CAD. A majority of sites overall (57.4%) and vascular-affiliated (72.7%) favored CEA. In contrast, radiology- and cardiology-affiliated sites demonstrated the highest proportion of sites favoring CAS, though they were equally likely to favor CEA. A large proportion (21/54, 38.9%) of sites received poor quality ratings (total DISCERN score <48), and the majority (41/54, 75.9%) required a reading level greater than a high school senior. CONCLUSIONS: CAD websites are often produced by government organizations, medical societies, or physicians, especially vascular surgeons. Sites ranged in quality, readability, and differentiation by symptomatic status. Google searches of CAD-related terms are more likely to yield sites favoring CEA. Future research should determine the extent of website influence on CAD patients' treatment decisions.
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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 | 0.017 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".