Late Stage Complicated Atheroma in Low-Grade Stenotic Carotid Disease: MR Imaging Depiction—Prevalence and Risk Factors
Bibliographic record
Abstract
PURPOSE: To determine if complicated plaque can be found by using magnetic resonance (MR) imaging-depicted intraplaque hemorrhage (IPH), even among symptomatic patients with low-grade (≤50%) carotid stenosis. MATERIALS AND METHODS: The institutional ethics review board approved this retrospective study and waived requirements for written informed consent. Symptomatic patients with bilateral 0%-50% carotid stenosis referred for carotid MR imaging were considered. Risk factors (age, sex, hypertension, diabetes, hyperlipidemia, myocardial infarction, atrial fibrillation, smoking, coronary artery disease, and cerebrovascular disease), medications (antihypertensive drugs, diabetes drugs, statins, and aspirin), and the brain side causing symptoms were recorded. MR-depicted IPH prevalence in the carotid arteries ipsilateral and contralateral to the symptomatic side was compared by using the Fisher exact test. Multivariable regression was used to compare the MR-depicted IPH prevalence, while adjusting for risk factors and medications. RESULTS: A total of 217 patients (434 carotid arteries) were included. MR-depicted IPH was found in 13% (31 of 233) of carotid arteries ipsilateral and 7% (14 of 201) of arteries contralateral to symptoms (P < .05). Male sex (P < .05) and increasing age (P < .05) were associated with MR-depicted IPH after controlling for risk factors and medications. CONCLUSION: Complicated carotid atheroma can be found among symptomatic patients with low-grade (≤50%) stenosis, and this is associated with male sex and increasing age. MR-depicted IPH may be useful to stratify risk for patients with low-grade carotid 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 | 0.001 | 0.003 |
| 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 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".