The effect of algae supplementation on lipid profile and blood pressure in adults: A systematic review and meta-analysis of randomized controlled trials
Bibliographic record
Abstract
• This systematic review and meta-analysis included 77 RCTs with 3686 participants. • Algae supplementation significantly reduced TG, TC, and LDL levels in adults. • Diastolic blood pressure significantly decreased with algae supplementation. • These findings suggest that algae supplementation can improve cardiovascular health markers. To assess the effects of algae supplementation on lipid profiles and blood pressure in adults, we conducted a systematic search in PubMed, Scopus, Web of Science, and Cochrane Library for relevant randomized controlled trials (RCTs). A total of 77 RCTs with 3686 participants were included. Algae supplementation significantly reduced triglycerides (TG) (WMD: −7.99 mg/dL, 95 % CI: −12.71, −3.26), total cholesterol (TC) (WMD: −11.01 mg/dL, 95 % CI: −14.26, −7.76), and low-density lipoprotein (LDL) (WMD: −10.17 mg/dL, 95 % CI: −13.12, −7.22) levels, while increasing high-density lipoprotein (HDL) (WMD: 1.66 mg/dL, 95 % CI: 0.73, 2.59). No significant changes were observed in the LDL/HDL ratio and systolic blood pressure (SBP), but diastolic blood pressure (DBP) significantly decreased (WMD: −1.71 mmHg, 95 % CI: −2.72, −0.71). These findings suggest that algae supplementation can improve cardiovascular health markers, although further research is needed to address the observed variability.
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 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 | 0.026 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.022 | 0.006 |
| 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 | 0.000 | 0.000 |
| 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".