Reduction of resistance artery stiffness by treatment with the AT1-receptor antagonist losartan in essential hypertension
Bibliographic record
Abstract
In spontaneously hypertensive rats resistance artery structure, endothelial dysfunction and geometry-independent wall stiffness were reduced by an angiotensin AT(1)-receptor antagonist. In previous studies of human hypertension, interruption of the renin-angiotensin system corrected small artery structure and endothelial dysfunction, whereas the beta-blocker atenolol did not. We hypothesized that the AT(1)R antagonist losartan, but not the beta-blocker atenolol, would reduce stiffness of gluteal subcutaneous small arteries in essential hypertensive patients. Seventeen untreated mild essential hypertensive patients (47+/-2 years; 75% male) were randomly assigned in double-blind fashion to losartan or atenolol treatment for one year. Small, resistance size arteries were studied on pressurized myographs. Blood pressure (mmHg) was reduced (p<0.01) from 145 +/- 4/101 +/- 2 and 147 +/- 6/98 +/- 2 to 128 +/- 4/86 +/- 2 and 131 +/- 3/84 +/- 1 by losartan and atenolol, respectively. The media/lumen ratio of small arteries was unaffected by atenolol (8.3+/-0.3% before and 8.8+/-0.5% after treatment). In contrast, losartan reduced media/lumen ratio from 8.4+/-0.4% to 6.7+/-0.3% (p<0.01). Whereas isobaric elastic modulus was unaffected by either treatment, geometry-independent stiffness (slope of elastic modulus vs. stress) was reduced from 9.7+/-1.2 to 6.1+/-0.9 (P<0.05) under losartan treatment, but was unchanged by atenolol (8.2+/-1.3 to 7.8+/-0.6). In conclusion, treatment with losartan reduced stiffness and structural alterations of subcutaneous resistance arteries of previously untreated essential hypertensive patients, whereas atenolol failed to do so.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".