LOW AMBULATORY DIASTOLIC BLOOD PRESSURE IS ASSOCIATED WITH BRAIN ATROPHY IN STRONGLY TREATED HYPERTENSIVE PATIENTS
Bibliographic record
Abstract
Objective: Despite optimal vascular risk factor control, older hypertensive and diabetic patients frequently develop cognitive decline and dementia. Cerebral small vessel disease (CSVD) contributes to cognitive decline, but the role of blood pressure (BP) control on brain atrophy remains controversial. We aimed to investigate whether systolic and diastolic BP control is associated with grey and white matter brain volume and whether brain volume reduction is associated with cognitive decline in hypertensive and diabetic patients. Design and method: Fifteen hypertensive patients (9 with diabetes mellitus), without previous stroke, underwent 24-hour ambulatory BP measurements and 1.5T cerebral magnetic resonance imaging. Cortical grey and white matter volumes were determined automatically using the Freesurfer® software. CSDV burden was assessed by calculating the age-related white matter changes (ARWMC) scale and the total small vessel disease (TSVD) score. The Mini- Mental State Examination (MMSE), Montreal Cognitive Assessmente (MoCA), digit span, Trail Making part B and Stroop tests were used to assess executive function performance. Gender, age, diabetic status, body mass index, pulse wave velocity and other significant comorbidities were used as potential confounders. Results: In this cohort of strongly treated (>3 drugs) hypertensive patients (age 66 ± 9.9 years, 56% male, 24 h systolic/diastolic BP = 140/84 ± 12/14 mmHg, nighttime BP = 130/78 ± 12/13 mmHg), lower 24 h diastolic BP was associated with greater cortical grey matter atrophy (24 hour: aR2 = 0.780, p = 0,001; daytime aR2 = 0.711, p = 0,002; nighttime: aR2 = 0.699, p = 0,004) and greater cortical white matter atrophy (daytime aR2 = 0.422, p = 0,047). Despite worse features vs general population, no correlation was found between subcortical grey matter volume, ARWMC or TSVD, scores brain volumes and systolic BP or nocturnal BP drop. Several cognitive measures significantly correlated with cortical grey and white matter volumes. Conclusions: We hypothesise that in strongly treated hypertensive older adults, low diastolic BP may exacerbate cerebral hypoperfusion and contribute to brain atrophy and cognitive decline, independent of CSDV burden. Larger samples are needed to confirm these results.
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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 | 0.001 |
| 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) | 0.002 | 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".