Angiotensin AT1-receptor blockers and cerebrovascular protection: do they actually have a cutting edge over angiotensin-converting enzyme inhibitors?
Bibliographic record
Abstract
First, an update of the vascular systemic and tissue renin-angiotensin-aldosterone system is provided to explain how it is regulated at the systemic and tissue levels, and how many angiotensin peptides and receptors can be modulated by the various antihypertensive drugs. Second, experimental data is presented to support the hypothesis that antihypertensive drugs that increase angiotensin II formation, such as diuretics, AT1-receptor blockers and dihydropyridines, may have greater brain anti-ischemic effects than antihypertensive drugs that decrease angiotensin II formation, such as beta-blockers and angiotensin-converting enzyme inhibitors, because they increase activation of angiotensin AT2 and AT4 receptors. Indeed, these trigger brain anti-ischemic mechanisms by favouring cerebral blood flow (angiogenesis and recruitment of pre-existing collateral circulation, specifically in the ischemic brain where AT2 receptors are overexpressed) or by directly increasing neuronal resistance to anoxia. Third, we review most of the large primary and secondary stroke prevention trials as well as the ACCESS acute stroke trial in which antihypertensive drugs were evaluated. With the exception of the secondary stroke prevention trial PRoFESS, most trials support the hypothesis that angiotensin II-increasing drugs confer specific blood pressure-independent brain ischemia protection when compared with angiotensin II-decreasing drugs or placebo. A careful analysis of the PRoFESS trial, however, reveals study design limitations, the main one being that diastolic BP (<80 mmHg) in the first month post-stroke may have been too low in at least one third of the population with baseline systolic blood pressure less than 130 mmHg, because a high dose of telmisartan was given after a very short post-stroke delay (median 15 days) without discontinuation of the baseline antihypertensive treatment.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".