Is High Blood Pressure Self-Protection for the Brain?
Bibliographic record
Abstract
RATIONALE: Data from animal models of hypertension indicate that high blood pressure may develop as a vital mechanism to maintain adequate blood flow to the brain. We propose that congenital vascular variants of the posterior cerebral circulation and cerebral hypoperfusion could partially explain the pathogenesis of essential hypertension, which remains enigmatic in 95% of patients. OBJECTIVE: To evaluate the role of the cerebral circulation in the pathophysiology of hypertension. METHODS AND RESULTS: We completed a series of retrospective and mechanistic case-control magnetic resonance imaging and physiological studies in normotensive and hypertensive humans (n=259). Interestingly, in humans with hypertension, we report a higher prevalence of congenital cerebrovascular variants; vertebral artery hypoplasia, and an incomplete posterior circle of Willis, which were coupled with increased cerebral vascular resistance, reduced cerebral blood flow, and a higher incidence of lacunar type infarcts. Causally, cerebral vascular resistance was elevated before the onset of hypertension and elevated sympathetic nerve activity (n=126). Interestingly, untreated hypertensive patients (n=20) had a cerebral blood flow similar to age-matched controls (n=28). However, participants receiving antihypertensive therapy (with blood pressure controlled below target levels) had reduced cerebral perfusion (n=19). Finally, elevated cerebral vascular resistance was a predictor of hypertension, suggesting that it may be a novel prognostic or diagnostic marker (n=126). CONCLUSIONS: Our data indicate that congenital cerebrovascular variants in the posterior circulation and the associated cerebral hypoperfusion may be a factor in triggering hypertension. Therefore, lowering blood pressure may worsen cerebral perfusion in susceptible individuals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.007 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".