Association of Cerebrovascular Reactivity With 1-Year Imaging and Clinical Outcomes in Small Vessel Disease
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: In patients with cerebral small vessel disease (SVD), impaired cerebrovascular reactivity (CVR) is related to worse concurrent SVD burden, but less is known about cerebrovascular reactivity and long-term SVD lesion progression and clinical outcomes. We investigated associations between cerebrovascular reactivity and 1-year progression of SVD features and clinical outcomes. METHODS: in subcortical gray matter, normal-appearing white matter, and white matter hyperintensities (WMH). At baseline and 1 year, we quantified SVD MRI features, incident infarcts, assessed stroke severity (NIH Stroke Scale), recurrent stroke, functional outcome (modified Rankin Scale), and cognition (Montreal Cognitive Assessment). We performed linear and logistic regressions adjusted for age, sex, and vascular risk factors, reporting the regression coefficients and odds ratios with 95% CIs. RESULTS: (%ROIV) per %/mm Hg), with a similar trend in WMH. CVR was not associated with clinical outcomes at 1 year. DISCUSSION: Lower baseline cerebrovascular reactivity predicted an increase in WMH and perivascular space volumes after 1 year. CVR should be considered in SVD future research and intervention studies.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".