The Realtionship Between Inflammation and Metabolic Syndrome (MetS)-A Matter of Gender?

作者
Adela Viviana Sitar Tǎut,Olga Orășan,Adriana Fodor,Anca Daniela Fărcaș,Simina Tarmure Sarlea,Gabriela Dogaru,Dumitru Zdrenghea,Dana Pop,Angela Cozma
出处
期刊: 卷期号:70 (1): 69-73 被引量:1
标识
DOI:10.37358/rc.19.1.6853
摘要

Were investigated the relationship between gender, cardiovascular risk factors and inflammation in metabolic syndrome (MetS) patients. 100 consecutive patients (75 women), 73 with MetS, mean age 57.52�9.77 years, were examined. Adhesion molecules (sICAM1, sVCAM1) were measured in the stored serum samples collected using the ELISA method. The classification of MetS was based on IDF guidelines. The study was carried out at the Department of Cardiology, Clinical Rehabilitation Hospital, Cluj-Napoca, Romania. MetS patients presented lower sICAM1 values (225.01�86.75 ng/mL vs 234.22�82.23 ng/mL, p=NS), but higher sVCAM1 values (605.34�298.69 ng/mL vs 552.29�233.77 ng/mL, p=NS). Differences between patients with vs without metabolic syndrome were found only in men for sICAM1 (194.73�37.92 ng/mL vs 282�27.15 ng/mL, p[0.001). Considering the HOMA index, a significant difference for sICAM1 was found in men (patients within the upper quartile vs the lower quartile, p=0.002), but also between women and men within the upper quartile of HOMA (for sICAM1 p=0.038). No significant differences were found for sVCAM1. In the case of males, sICAM1 was an independent predictor of metabolic syndrome, with a very good capacity to identify metabolic syndrome (AUROC=0.987, p=0.0001, Se=89.47%, Sp=100%). In conclusion, just in men, sICAM1 seems to have an excellent capacity to differentiate between MetS+ and MetS- patients, to predict MetS development.

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
燕天与完成签到,获得积分20
刚刚
唯梦发布了新的文献求助10
刚刚
Yu发布了新的文献求助10
1秒前
2秒前
2秒前
3秒前
wz完成签到,获得积分10
4秒前
蓝天应助梨花弦外雨采纳,获得10
4秒前
4秒前
板板完成签到 ,获得积分10
4秒前
希望天下0贩的0应助ii采纳,获得10
4秒前
4秒前
明明发布了新的文献求助20
5秒前
5秒前
desperado发布了新的文献求助10
6秒前
6秒前
6秒前
和谐夏彤发布了新的文献求助20
7秒前
7秒前
尕辉发布了新的文献求助10
8秒前
板板关注了科研通微信公众号
8秒前
8秒前
lius发布了新的文献求助10
8秒前
lynn完成签到 ,获得积分20
8秒前
11111111应助留胡子的项链采纳,获得10
8秒前
lihaoyu发布了新的文献求助10
9秒前
MBM发布了新的文献求助10
9秒前
Mic应助背后的夜梅采纳,获得30
9秒前
七昂完成签到,获得积分10
9秒前
laola驳回了慕青应助
10秒前
Jasper应助Yu采纳,获得10
10秒前
11秒前
11秒前
君看一叶舟完成签到,获得积分10
11秒前
李健应助瑞达采纳,获得10
11秒前
优美薯片发布了新的文献求助10
12秒前
Cole发布了新的文献求助10
12秒前
科研通AI6.4应助你好采纳,获得10
12秒前
英俊的铭应助l林采纳,获得10
12秒前
12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
48V Low-voltage Power Distribution Network (PDN) Architecture Industry Report, 2024 800
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
适配Micro-LED色转换的高兼容性量子点负性光刻胶制备与工艺研究 500
Direct and Iterative Linear System Solvers 500
Vander's Renal Physiology第10版 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 7308485
求助须知:如何正确求助?哪些是违规求助? 8926002
关于积分的说明 18916103
捐赠科研通 6970983
什么是DOI,文献DOI怎么找? 3212820
关于科研通互助平台的介绍 2381348
邀请新用户注册赠送积分活动 2190568