Emerging role of angiotensin II type 1 receptor blockers for the treatment of endothelial dysfunction and vascular inflammation.
Bibliographic record
Abstract
BACKGROUND: Angiotensin II type 1 receptor blockers (AT1RBs) share the effect of attenuating angiotensin II actions with angiotensin-converting enzyme inhibitors (ACEIs) but differ in other respects. Notably, the impact of unopposed angiotensin type 2 receptor stimulation and the absence of augmentation of bradykinin through inhibition of the kininase pathway may lead to differences between the effects of AT1RBs and ACEIs. ACEIs have been shown to improve endothelial dysfunction in many clinical settings. OBJECTIVE: To review current evidence regarding the effects of AT1RBs on endothelial dysfunction in patients. METHODS: MEDLINE and Current Contents searches, augmented by careful analyses of the bibliographies in the identified papers, were used to identify studies assessing the effects of chronic, oral use of AT1RBs on endothelial function and related inflammatory markers in patients. Animal studies and human studies using single doses or intravenous infusions were excluded. RESULTS: Clinical studies are available pertaining to the elderly and patients with coronary artery disease, hypertension and diabetes. The effect on endothelial dysfunction induced by postprandial lipemia has also been assessed. In general, AT1RBs improve vasomotor endothelial dysfunction and some inflammatory markers, but a few studies comparing ACEIs directly with AT1RBs suggest that AT1RBs may be inferior. AT1RB activity on endothelial dysfunction in patients with type I diabetes has not been shown. CONCLUSIONS: AT1RBs are an important addition to the therapy of endothelial dysfunction and vascular inflammation in patients. Further research is necessary to determine which AT1RBs and which dosing regimens are optimal.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".