Effect of oat β-glucan in managing blood pressure: a randomized cross-over pilot trial
Bibliographic record
Abstract
Hypertension affects over 1.2 billion adults worldwide. While numerous pharmacological treatments are available for managing hypertension, dietary approaches may also offer beneficial alternatives or complementary strategies. High molecular weight (HMW) β-glucan, a fibre found in oats, may be responsible for reductions in systolic blood pressure. This pilot trial investigated the efficacy of HMW oat β-glucan in reducing systolic and diastolic blood pressure in individuals with mild hypertension. Additionally, changes in heart rate, body weight, waist circumference, and dietary intake, including protein, carbohydrates, fat, and fibre were assessed. This study was conducted virtually during the COVID-19 pandemic. The trial followed a randomized, double-blinded, cross-over design. During the treatment period, participants were provided breakfast cookies made from oats containing 4 g/day of HMW oat β-glucan. During the control period, participants received breakfast cookies made primarily from wheat, which does not contain a significant amount of β-glucan (0.12 g/day). Twenty-one people completed the trial. Consumption of oat β-glucan breakfast cookies for 4 weeks did not reduce systolic blood pressure (132.71 ± 1.92 vs. 132.9 ± 1.92, p = 0.95) or diastolic blood pressure (82.86 ± 1.43 vs. 82.38 ± 1.43, p = 0.98) compared to control. Waist circumference ( p = 0.67), weight ( p = 0.79), heart rate ( p = 0.73), and dietary intake (protein ( p = 29), carbohydrate ( p = 0.45), fat ( p = 12), and fibre ( p = 0.64)) were unchanged. Our results indicate that oat β-glucan consumption does not affect systolic or diastolic blood pressure compared to a wheat-based control in middle age and older adults with mild hypertension.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.007 | 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".