The effectiveness of intervention with omega-3 fatty acids, eicosapentaenoic and docosahexenoic acid in peripheral arterial disease: a systematic review and meta-analysis
Bibliographic record
Abstract
AIMS: Omega-3 polyunsaturated fatty acids are routinely recommended as a lifestyle modification for preventing cardiovascular disease (CVD). It is not clear if any omega-3 polyunsaturated fatty acid formulations are favourable for patients with peripheral artery disease (PAD). DATA SYNTHESIS: A systematic review and meta-analysis (PROSPERO registration ID CRD42022336641) was conducted to determine the effects of omega-3 fatty acids on functional outcomes in people with PAD. Studies reporting any dose of eicosapentaenoic acid (EPA) or docosahexaenoic acid (DHA) supplementation versus placebo were assessed by two independent reviewers. Data including study design, number, age and sex of participants, period of assessment, diagnosis method for PAD, inclusion and exclusion criteria, method and formulation of omega-3 supplementation were analysed. Risk of bias was determined using the Newcastle-Ottawa scale. Of 1067 citations, 12 studies (n = 759 patients) met the predefined inclusion criteria. Supplementation of EPA, or EPA + DHA did not alter the primary outcome measures of pain-free walking distance, maximal walking distance; ankle brachial index, or flow mediated vasodilation versus placebo. There were no changes in secondary outcomes of circulating inflammatory markers, cholesterol, or blood pressure. CONCLUSION: Mixed omega-3 fatty acids, especially in low doses, are not effective in reducing symptoms of PAD. However, there is insufficient evidence to rule out effectiveness of specific omega 3 formulations, particularly for high-risk populations. Therefore, it is recommended that a large scale, randomised control trial with high dose EPA is conducted in patients with PAD.
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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 | 0.014 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.038 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".