The impact of argan oil on plasma lipids in humans: Systematic review and meta‐analysis of randomized controlled trials
Bibliographic record
Abstract
The study aims to investigate the effect of argan oil on plasma lipid concentrations through a systematic review of the literature and a meta-analysis of available randomized controlled trials. Randomized controlled trials that investigated the impact of at least 2 weeks of supplementation with argan oil on plasma/serum concentrations of at least 1 of the main lipid parameters were eligible for inclusion. Effect size was expressed as the weighted mean difference (WMD) and 95% confidence interval (95% CI). Meta-analysis of data from 5 eligible trials with 292 participants showed a significant reduction in plasma concentrations of total cholesterol (WMD: -16.85 mg/dl, 95% CI [-25.10, -8.60], p < .001), low-density lipoprotein cholesterol (WMD: -11.67 mg/dl, 95% CI [-17.32, -6.01], p < .001), and triglycerides (WMD: -13.69 mg/dl, 95% CI [-25.80, -1.58], p = .027) after supplementation with argan oil compared with control treatment, and plasma concentrations of high-density lipoprotein cholesterol (WMD: 4.14 mg/dl, 95% CI [0.86, 7.41], p = .013) were found to be increased. Argan oil supplementation reduces total cholesterol, low-density lipoprotein cholesterol, and triglycerides and increases high-density lipoprotein cholesterol levels. Additionally, larger clinical trials are needed to assess the impact of argan oil supplementation on other indices of cardiometabolic risk and on the risk of cardiovascular outcomes.
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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 | 0.021 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.031 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".