No Difference between the Efficacy of High-Nitrate and Low-Nitrate Vegetable Supplementation on Blood Pressure after 16 Weeks in Individuals with Early-Stage Hypertension: An Exploratory, Double-Blinded, Randomized, Controlled Trial
Bibliographic record
Abstract
Dietary inorganic nitrate lowers blood pressure (BP) in healthy individuals through improved nitric oxide (NO) bioavailability. However, there is limited evidence examining the long-term effects of dietary nitrate for managing hypertension. We aimed to determine whether the sustained intake of dietary nitrate improved BP and cardiovascular disease (CVD) risk factors in individuals with early-stage hypertension. The Dietary Nitrate (NO3) on BP and CVD Risk Factors (DINO3) Trial was a multi-center, double-blinded, parallel, randomized, controlled trial in participants with elevated BP. Participants were supplemented with high-nitrate (HN) (~400 mg nitrate) or low-nitrate (LN) vegetable powder (~50 mg nitrate) on top of their usual diets for 16 weeks. The primary outcome was office systolic BP at 16 weeks. The secondary outcomes were 24 h ambulatory BP, central BP, heart-rate-corrected augmentation index (AIx75), carotid–femoral pulse wave velocity (cf-PWV), lipids, and high-sensitivity C-reactive protein (hs-CRP). Sixty-six participants were randomized at baseline (39M:27F, age: 51.5 ± 10.8 years, BMI:27.9 ± 3.2 kg/m2). In an intention-to-treat analysis, no differences were observed between HN and LN groups in terms of office systolic BP at 16 weeks (3.91 ± 3.52 mmHg, p = 0.27) or secondary outcomes. In this exploratory study, sustained HN vegetable supplementation did not exhibit more favorable vascular effects than LN vegetable supplementation in individuals with elevated BP.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 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 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".