Abstract 061: Continuous And Cyclic Components Of Blood Pressure Profile Have Impact On Different Brain Areas In Controlled Hypertensive Patients
Bibliographic record
Abstract
Increase in arterial blood pressure consistently damages the connectivity and function of the brain. While this evidence is becoming more widely accepted, the effects of daily fluctuations and variability in blood pressure levels on the brain are still not well understood. Our study investigated the impact of blood pressure variability (BPV) on cognitive function and white matter brain structure in a cohort of hypertensive patients under optimal BP control. We used diffusion tensor imaging (DTI-MRI) to assess white matter injury, neuropsychological tests such as the Montreal Cognitive Assessment (MoCA) to evaluate cognitive function, and 24-hour ambulatory blood pressure monitoring to measure BPV. Spectral analysis of BPV allowed us to measure both the cyclic and the continuous components of arterial blood pressure profile. We found that the Fractional Anisotropy of the Middle Cerebellar Peduncle was correlated with the cyclic component of both diastolic and systolic blood pressure. Additionally, a significant association between the continuous component of both diastolic and systolic blood pressure and the Anterior Thalamic Radiation was detected.. Finally, cognitive functions measured by MoCA were correlated with the continuous component of both diastolic and systolic blood pressure (Table). Our results suggest that the continuous component of blood pressure negatively impacts white matter regions associated with cognitive impairment, while the cyclic component is associated with alterations in brainstem regions where nervous vagal control is coordinated.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".