Isoflavones and Clinical Cardiovascular Risk Factors in Obese Postmenopausal Women: A Randomized Double-Blind Placebo-Controlled Trial
Bibliographic record
Abstract
AIMS: To investigate whether 6 months of isoflavone supplementation, which has been shown to be sufficient to improve menopausal symptoms, could also improve clinical cardiovascular disease (CVD) risk factors in obese postmenopausal women, compared with a placebo. METHODS: A randomized double-blind placebo-controlled trial in which 50 obese postmenopausal women were divided into two groups (isoflavones vs. placebo) to examine the effect of 6 months of isoflavone supplement (70 mg) on clinical CVD risk factors. Body composition (DXA), medical and social characteristics, daily energy expenditure (accelerometry), dietary intake (3-day dietary record), and blood biochemical analyses (lipid profile, insulin, glucose) were obtained. RESULTS: At baseline, no differences were found between groups except for fasting insulin level. Women were thus considered at risk of CVD based on body composition but not biochemical variables. After 6 months, we observed that isoflavones did not favorably affect risk factors predisposing to CVD (biochemical or body composition) compared with placebo. CONCLUSIONS: Isoflavones given for 6 months should not be considered protective against clinical CVD risk factors in obese postmenopausal women. Nevertheless, further research is needed to verify if isoflavones protect against CVD disease risk factors when administered for a longer duration or when combined with nutritional or exercise interventions. It would also be pertinent to study their effects in women with specific metabolic abnormalities.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 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 | 0.000 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".