Changes in Aortic Stiffness and Augmentation Index After Acute Converting Enzyme or Vasopeptidase Inhibition
Bibliographic record
Abstract
Augmentation index (AI), a measure of enhanced wave reflection, has been proposed as a bedside measure of aortic stiffness. However, because AI is potentially sensitive to various factors other than vessel wall stiffness, the utility of AI as a stiffness indicator may be limited. To assess relations between AI and vascular properties, we used arterial tonometry and aortic Doppler flow to evaluate trough (24 hours) and peak (4 hours) pulsatile hemodynamics and pulse wave velocity in 159 individuals with systolic hypertension at the completion of a 12-week period of monotherapy with the vasopeptidase inhibitor omapatrilat (80 mg; n=75) or the converting enzyme inhibitor enalapril (40 mg; n=84). Characteristic impedance (Zc) was calculated from the ratio of change in carotid pressure and aortic flow in early systole. Systolic ejection period (SEP), timing of wave reflection, and AI were assessed from the carotid waveform. Comparable acute reductions in mean pressure were associated with greater reductions in peripheral resistance with enalapril, whereas neither drug had an acute effect on Zc. Both drugs reduced AI, but neither drug altered the timing of wave reflection. Both drugs increased heart rate and shortened SEP. Multiple regression analysis demonstrated that the acute reduction in AI was most affected by reductions in SEP and peripheral resistance. Change in AI was inversely related to change in Zc and pulse wave velocity did not enter the model. Our findings indicate that AI is a complex surrogate marker that is inversely related to changes in proximal aortic stiffness in systolic hypertension.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".