The effects of citrus flavonoids supplementation on endothelial function: A systematic review and dose–response meta‐analysis of randomized clinical trials

荟萃分析 医学 合并分析 安慰剂 随机对照试验 内科学 置信区间 随机效应模型 科学网 替代医学 病理
作者
Farnaz Jalili,Farnaz Jalili,Sajjad Moradi,Sepide Talebi,Sanaz Mehrabani,Seyed Mojtaba Ghoreishy,Alexei Wong,Ali R. Jalalvand,Mohammad Ali Hojjati Kermani,Cyrus Jalili,Faramarz Jalili,Faramarz Jalili
出处
期刊:Phytotherapy Research [Wiley]
卷期号:38 (6): 2847-2859 被引量:14
标识
DOI:10.1002/ptr.8190
摘要

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; I 2 = 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; I 2 = 94.5%; p < 0.001). The findings from the nonlinear dose–response analysis also revealed a linear relationship between CFS and FMD ( P non‐linearity = 0.903, P dose–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.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
1秒前
2秒前
魏佳阁发布了新的文献求助10
3秒前
renshiq发布了新的文献求助10
4秒前
Lucky完成签到 ,获得积分10
6秒前
任白993应助NiL采纳,获得10
6秒前
轻松念之完成签到,获得积分10
7秒前
搜集达人应助suntreenew采纳,获得10
7秒前
乐枳完成签到,获得积分10
8秒前
尤静柏完成签到,获得积分10
9秒前
9秒前
调皮曼冬完成签到,获得积分10
10秒前
情怀应助沉静的樱桃采纳,获得10
13秒前
gengwenjing发布了新的文献求助10
14秒前
荔枝发布了新的文献求助10
15秒前
博比完成签到,获得积分10
15秒前
浮星凡羽完成签到,获得积分10
16秒前
16秒前
冷静新柔完成签到,获得积分10
20秒前
传奇3应助科研通管家采纳,获得10
20秒前
科目三应助科研通管家采纳,获得10
20秒前
香蕉觅云应助科研通管家采纳,获得30
21秒前
21秒前
酷波er应助科研通管家采纳,获得10
21秒前
Tian完成签到,获得积分10
21秒前
充电宝应助科研通管家采纳,获得10
21秒前
隐形曼青应助科研通管家采纳,获得10
21秒前
Dean应助科研通管家采纳,获得50
21秒前
明亮夜云完成签到,获得积分10
22秒前
22秒前
22秒前
Kao应助科研通管家采纳,获得10
22秒前
Owen应助科研通管家采纳,获得10
22秒前
锅包又完成签到 ,获得积分10
22秒前
sagitar应助科研通管家采纳,获得20
22秒前
22秒前
NexusExplorer应助科研通管家采纳,获得10
22秒前
完美世界应助科研通管家采纳,获得10
23秒前
深情安青应助科研通管家采纳,获得10
24秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Health Psychology 800
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Electric machines: theory, operating applications, and controls 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
When Is Two-Stage Sample Robust Optimization Asymptotically Optimal? 500
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7593046
求助须知:如何正确求助?哪些是违规求助? 9170282
关于积分的说明 19627955
捐赠科研通 7170993
什么是DOI,文献DOI怎么找? 3267554
关于科研通互助平台的介绍 2432418
邀请新用户注册赠送积分活动 2260134