Brain White Matter Hyperintensities Are Associated with Carotid Intraplaque Hemorrhage
Bibliographic record
Abstract
PURPOSE: To retrospectively assess the relationship between carotid intraplaque hemorrhage (IPH), which indicates plaque instability, and brain white matter hyperintense lesions (WMHLs) by using a within-patient design. MATERIALS AND METHODS: All patients gave written informed consent for the initial magnetic resonance (MR) studies, and the institutional review board and local research ethics committee waived initial informed consent for the pooled analysis. A total of 190 patients with symptomatic carotid artery disease underwent fluid-attenuated inversion-recovery imaging of the brain and fat-suppressed black-blood T1-weighted MR imaging of the carotid arteries. The volumes of periventricular lesions, subcortical lesions, and total WMHLs were calculated and compared between hemispheres in relation to symptoms and IPH, and their interaction was calculated and compared by using repeated measures three-factorial multivariate analysis. RESULTS: After exclusion of 12 patients, 178 patients (116 men, 62 women; mean age, 70.2 years +/- 8.6 [standard deviation]) remained. There was no significant difference in WMHL volume between the symptomatic and asymptomatic hemispheres, and WMHL volume was not related to the degree of carotid stenosis. The presence of carotid IPH significantly interacted with the interhemispheric WMHL difference (Wilks lambda test, F = 9.95; df = 3; P < .001). Univariate analysis showed larger total and periventricular WMHL volumes (P < .05) in patients with ipsilateral IPH. CONCLUSION: Carotid artery disease and leukoaraiosis were associated with features that indicated plaque instability, namely IPH, whereas the degree of stenosis had no effect.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".