Effect of Azilsartan on Day-to-Day Variability in Home Blood Pressure: A Prospective Multicenter Clinical Trial
Bibliographic record
Abstract
BACKGROUND: The blood pressure variability (BPV) such as visit-to-visit, day-by-day, and ambulatory BPV has been also shown to be a risk of future cardiovascular events. However, the effects of antihypertensive therapy on BPV remain unclear. The purpose of this study was to evaluate the effect of azilsartan after switching from another angiotensin II receptor blocker (ARB) on day-to-day BPV in home BP monitoring. METHODS: This prospective, multicenter, open-labeled, single-arm study included 28 patients undergoing treatment with an ARB, which was switched to azilsartan after enrollment. The primary outcome was the change in the mean of the standard deviation and the coefficient of variation of morning home BP for 5 consecutive days from baseline to the 24-week follow-up. The secondary outcome was the change in arterial stiffness measured by the cardio-ankle vascular index. RESULTS: The mean BPs in the morning and evening for 5 days did not statistically differ between baseline and 24 weeks. For the morning BP, the means of the standard deviations and coefficient of variation of the systolic BP were significantly decreased from 7.4 ± 3.6 mm Hg to 6.1 ± 3.2 mm Hg and from 5.4±2.7% to 4.6±2.3% (mean ± standard deviation, P = 0.04 and P = 0.04, respectively). For the evening BP, no significant change was observed in the systolic or diastolic BPV. The cardio-ankle vascular index significantly decreased from 8.3 ± 0.8 to 8.1 ± 0.8 (P = 0.03). CONCLUSIONS: Switching from another ARB to azilsartan reduced day-to-day BPV in the morning and improved arterial stiffness.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".