The effects of citrus flavonoids supplementation on endothelial function: A systematic review and dose–response meta‐analysis of randomized clinical trials
Bibliographic record
Abstract
Abstract The present systematic review and dose–response meta‐analysis was conducted to synthesize existing data from randomized clinical trials (RCTs) concerning the impact of citrus flavonoids supplementation (CFS) on endothelial function. Relevant RCTs were identified through comprehensive searches of the PubMed, ISI Web of Science, and Scopus databases up to May 30, 2023. Weighted mean differences and their corresponding 95% confidence intervals (CI) were pooled utilizing a random‐effects model. A total of eight eligible RCTs, comprising 596 participants, were included in the analysis. The pooled data demonstrated a statistically significant augmentation in flow‐mediated vasodilation (FMD) (2.75%; 95% CI: 1.29, 4.20; I2 = 87.3%; p < 0.001) associated with CFS compared to the placebo group. Furthermore, the linear dose–response analysis indicated that each increment of 200 mg/d in CFS led to an increase of 1.09% in FMD (95% CI: 0.70, 1.48; I2 = 94.5%; p < 0.001). The findings from the nonlinear dose–response analysis also revealed a linear relationship between CFS and FMD (Pnon‐linearity = 0.903, Pdose–response <0.001). Our findings suggest that CFS enhances endothelial function. However, more extensive RTCs encompassing longer intervention durations and different populations are warranted to establish more precise conclusions.
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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 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.036 |
| Bibliometrics | 0.005 | 0.005 |
| 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) | 0.004 | 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".