Longitudinal relation between blood pressure, antihypertensive use and cerebral blood flow, using arterial spin labelling MRI
Bibliographic record
Abstract
Consistent cerebral blood flow (CBF) is fundamental to brain function. Cerebral autoregulation ensures CBF stability. Chronic hypertension can lead to disrupted cerebral autoregulation in older people, potentially leading to blood pressure levels interfering with CBF. This study tested whether low BP and AHD use are associated with contemporaneous low CBF, and whether longitudinal change in BP is associated with change in CBF, using arterial spin labelling (ASL) MRI, in a prospective longitudinal cohort of 186 community-dwelling older individuals with hypertension (77 ± 3 years, 53% female), 125 (67%) of whom with 3-year follow-up. Diastolic blood pressure, systolic blood pressure, mean arterial pressure, and pulse pressure were assessed as blood pressure parameters. As additional cerebrovascular marker, we evaluated the ASL signal spatial coefficient of variation (ASL SCoV), a measure of ASL signal heterogeneity that may reflect cerebrovascular health. We found no associations between any of the blood pressure measures and concurrent CBF nor between changes in blood pressure measures and CBF over three-year follow-up. Antihypertensive use was associated with lower grey matter CBF (−5.49 ml/100 g/min, 95%CI = −10.7|−0.27, p = 0.04) and higher ASL SCoV (0.32 SD, 95%CI = 0.12|0.52, p = 0.002). These results warrant future research on the potential relations between antihypertensive use and cerebral perfusion.
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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 | 0.001 |
| 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) | 0.001 | 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".