Angiotensin II type 1 receptor antagonists in the treatment of hypertension in elderly patients: focus on patient outcomes
Bibliographic record
Abstract
Artavazd Tadevosyan1, Eric J MacLaughlin2, Vardan T Karamyan31Departments of Medicine, Montreal Heart Institute and Université de Montréal, Montreal, QC, Canada; 2Department of Pharmacy Practice, 3Department of Pharmaceutical Sciences, School of Pharmacy, Texas Tech University Health Sciences Center, Amarillo, TX, USAAbstract: Hypertension in the elderly is one of the main risk factors of cardiovascular and cerebrovascular diseases. Knowledge regarding the mechanisms of hypertension and specific considerations in managing hypertensive elderly through pharmacological intervention(s) is fundamental to improving clinical outcomes. Recent clinical studies in the elderly have provided evidence that angiotensin II type 1 (AT1) receptor antagonists can improve clinical outcomes to a similar or, in certain populations, an even greater extent than other classical arterial blood pressure-lowering agents. This newer class of antihypertensive agents presents several benefits, including potential for improved adherence, excellent tolerability profile with minimal first-dose hypotension, and a low incidence of adverse effects. Thus, AT1 receptor antagonists represent an appropriate option for many elderly patients with hypertension, type 2 diabetes, heart failure, and/or left ventricular dysfunction.Keywords: angiotensin II, ARB, cardiovascular disease, antihypertensive therapy, elderly
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".