Stroke Risk Profile Predicts White Matter Hyperintensity Volume
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Previous studies of cardiovascular risk factors and white matter hyperintensity (WMH) on brain MRI have been limited by the failure to exclude symptomatic cerebrovascular disease and dementia or by the use of semiquantitative rather than quantitative methods to measure WMH volume (WMHV). We examined the relationship between Framingham Stroke Risk Profile (FSRP) and WMHV measured quantitatively in a stroke and dementia-free subset of the Framingham Offspring Cohort. METHODS: Brain MRI was performed in 1814 members of the Framingham Offspring Cohort. Pixel-based quantitative measures of WMHV corrected for head size were obtained using a semiautomated algorithm. WMHV was not normally distributed and therefore was log-transformed (LWMHV). The FSRP and its component risk factors measured a mean of 7.5 years before MRI were related to both continuous measures of LWMHV and to the presence of large volumes of LWMHV (LWMHV-large). All analyses were adjusted for age and sex. RESULTS: FSRP was strongly associated with LWMHV and LWMHV-large. Age, smoking, history of cardiovascular disease, hypertension, and left ventricular hypertrophy by electrocardiogram were all significantly related to LWMHV or LWMHV-large. CONCLUSIONS: FSRP and several cardiovascular risk factors were related to both WMHV measured continuously and to a categorical designation of large volumes of WMH. These findings provide strong evidence of a vascular basis for WMH.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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 it