Eicosapentaenoic acid and docosahexaenoic acid containing supplements modulate risk factors for cardiovascular disease: a meta‐analysis of randomised placebo‐control human clinical trials
Bibliographic record
Abstract
Abstract Background Over 200 clinical trials have examined the effect of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) supplements on risk factors associated with cardiovascular disease. However, an updated analysis of the evidence is lacking. The aim of the present meta‐analysis was to quantify the effect of supplements containing EPA and DHA on risk factors for cardiovascular disease. Methods An analysis was carried on 171 clinical trials with acceptable quality (Jadad score ≥3) that were identified from a comprehensive electronic search strategy of two databases (Pubmed and Cochrane Library). A random effect model was used to obtain an overall estimate on outcomes of interest. Heterogeneity between trial results was tested for using a standard chi‐squared test. Results Compared with control, EPA and DHA supplements produced significant reductions of triglycerides of 0.368 mmol L−1 [95% confidence interval (CI) = −0.427 to −0.309], systolic blood pressure of 2.195 mmHg (95% CI = −3.172 to −1.217), diastolic blood pressure of 1.08 mmHg (95% CI = −1.716 to −0.444), heart rate of 1.37 bpm (95% CI = −2.41 to −0.325) and C‐reactive protein of 0.343 mg L−1 (95% CI = −0.454 to −0.232). This analysis indicates an increase in both low‐density lipoprotein cholesterol (mean difference = 0.150 mmol L−1; 95% CI = 0.058–0.243) and high‐density lipoprotein cholesterol (mean difference = 0.039 mmol L−1; 95% CI = 0.024–0.054). The triglyceride‐lowering effect was dose‐dependent. Conclusions The lipid‐lowering, hypotensive, anti‐arrhythmic and anti‐inflammatory actions of EPA and DHA supplements were confirmed in this analysis of randomised placebo‐control blinded clinical trials.
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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 | 0.023 | 0.039 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.042 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".