The Effects of the Dietary Supplement Cardioflex on Reducing Cardiovascular Disease Risk Factors in Adults
Bibliographic record
Abstract
The overall objective was to determine the effects of the multi-nutrient dietary supplement Cardioflex, independent of diet or lifestyle changes, to reduce cardiovascular disease (CVD) risk factors in adults. A 90-day, randomized, double-blind, parallel design clinical study was performed from February to June 2019. Participants received one serving (10 g) of Cardioflex or an isocaloric maltodextrin placebo daily. Blood pressure was measured using an automatic sphygmomanometer. A 1-min arterial test (accelerated plethysmography; APG) and a 5-min heart-rate-variability (HRV) test were conducted using a Meridian digital pulse wave analyzer. Serum concentrations of total cholesterol (TC), triglycerides (TG) and high-density lipoprotein (HDL) were measured using Vitros-350 chemistry analyzer. Analysis of covariance was used to compare the post treatment biomarkers of the two groups using IBM SPSS Statistics (v.25). A total of 67 participants (placebo = 33, Cardioflex = 34) with a mean age of 48.3 ± 8.8 years, completed the study. Cardioflex improved HRV (+5%; P = 0.04) compared to the placebo (−9%). Although both groups saw improvements in blood pressure, heart rate, APG age, body mass index, waist circumference, TC, low-density lipoprotein (LDL), and TG, there was no significant difference (P > 0.05) between groups. Interestingly, the placebo significantly (P = 0.04) lowered (−18.7%) TC compared to Cardioflex (−15%). Cardioflex supplement may benefit HRV; a parameter associated with CVD. However, more research is needed to understand its effects on CVD. Also, our study also highlights the ‘placebo effect’ that can occur in parallel design clinical trials. Funding was provided by MITACs and Innotech Nutrition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".