Clinical effectiveness of telmisartan alone or in combination therapy for controlling blood pressure and vascular risk in the elderly
Bibliographic record
Abstract
Elderly patients (age ≥ 65 years) with hypertension are at high risk for vascular complications, especially when diabetes is present. Antihypertensive drugs that inhibit the renin-angiotensin system have been shown to be effective for controlling blood pressure in adult and elderly patients. Importantly, renin-angiotensin system inhibitors were shown to have benefits beyond their classic cardioprotective and vasculoprotective effects, including reducing the risk of new-onset diabetes and associated cardiovascular effects. The discovery that the renin-angiotensin system inhibitor and angiotensin II type 1 (AT(1)) receptor blocker (ARB), telmisartan, can selectively activate the peroxisome proliferator-activated receptor-γ (PPARγ, an established antidiabetic drug target) provides the unique opportunity to prevent and treat cardiovascular complications in high-risk elderly patients with hypertension and new-onset diabetes. Two large clinical trials, ONTARGET (Ongoing Telmisartan Alone in combination with Ramipril Global Endpoint Trial) and TRANSCEND (Telmisartan Randomized AssessmeNt Study in ACE-I iNtolerant subjects with cardiovascular disease) have assessed the cardioprotective and antidiabetic effects of telmisartan. The collective data suggest that telmisartan is a promising drug for controlling hypertension and reducing vascular risk in high-risk elderly patients with new-onset diabetes.
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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 | 0.002 | 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) | 0.004 | 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".