Interactions of commonly used dietary supplements with cardiovascular drugs: a systematic review
Bibliographic record
Abstract
BACKGROUND: The objective of this systematic review was to examine the benefits, harms and pharmacokinetic interactions arising from the co-administration of commonly used dietary supplements with cardiovascular drugs. Many patients on cardiovascular drugs take dietary supplements for presumed benefits and may be at risk for adverse supplement-drug interactions. METHODS: The Allied and Complementary Medicine Database, the Cochrane Library, EMBASE, International Bibliographic Information on Dietary Supplements and MEDLINE were searched from the inception of the review to October 2011. Grey literature was also reviewed.Two reviewers independently screened records to identify studies comparing a supplement plus cardiovascular drug(s) with the drug(s) alone. Reviewers extracted data using standardized forms, assessed the study risk of bias, graded the strength of evidence and reported applicability. RESULTS: Evidence was obtained from 65 randomized clinical trials, 2 controlled clinical trials and 1 observational study. With only a few small studies available per supplement, evidence was insufficient for all predefined gradable clinical efficacy and harms outcomes, such as mortality and serious adverse events. One long-term pragmatic trial showed no benefit from co-administering vitamin E with aspirin on a composite cardiovascular outcome. Evidence for most intermediate outcomes was insufficient or of low strength, suggesting no effect. Incremental benefits were noted for triglyceridemia with omega-3 fatty acid added to statins; and there was an improvement in levels of high-density lipoprotein cholesterol with garlic supplementation when people also consumed nitrates CONCLUSIONS: Evidence of low-strength indicates benefits of omega-3 fatty acids (plus statin, or calcium channel blockers and antiplatelets) and garlic (plus nitrates or warfarin) on triglycerides and HDL-C, respectively. Safety concerns, however, persist.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.030 | 0.005 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".