Effects of Korean White Ginseng (Panax Ginseng C.A. Meyer) on Vascular and Glycemic Health in Type 2 Diabetes: Results of a Randomized, Double Blind, Placebo-controlled, Multiple-crossover, Acute Dose Escalation Trial
Bibliographic record
Abstract
UNLABELLED: Korean red ginseng (steam treated Panax ginseng C.A. Meyer), among most prized traditional herbal remedies, has been clinically shown to improve cardiovascular disease (CVD) risk factors. Whether this holds true for the dried non-steamed variety, known as Korean white ginseng (KWG) is unclear. This study therefore, investigated the efficacy and safety of escalating doses of KWG on vascular and glycemic parameters in type 2 diabetes (T2DM). Using an acute, randomized, placebo-controlled, double-blind, crossover design, 25 participants with well-controlled T2DM (12-males: 13-females, age: 63 ± 9 years, A1c: 6.9 ± 0.7%, BMI: 29.3 ± 4.3 kg/m(2)) underwent five visits during which they received 1 g, 3 g, or 6 g KWG or 3 g wheat-bran control (twice) together with 50 g-glucose load. For the duration of 240 minutes, augmentation index (AI), and central blood pressure were measured at baseline and at 60 min-intervals, and ambulatory blood pressure was assessed at baseline and at 10 min-intervals. Additionally, capillary blood was collected at time zero and at 15, 30, 45, 60, 90, 120, and 180 minutes post-treatment. A symptoms questionnaire was used to assess safety and adverse events. Two-way ANOVA demonstrated a significant time-treatment interaction effect on AI (p = 0.01) with one-way ANOVA showing significant reductions in AI with 3 g KWG relative to control (p = 0.04). Compared to control, acute administration of KWG appeared to be safe, but did not affect any other postprandial, vascular or glycemic parameters. KWG might have a beneficial effect on AI, a cumulative indicator of arterial health. However, these results are preliminary and highlight the need for long-term investigation with a focus on its accountable components. CLINICAL TRIAL REGISTRATION: NCT01699074.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".