亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Metabolic health and cardiometabolic risk clusters: implications for prediction, prevention, and treatment

医学 人体测量学 代谢综合征 肥胖 风险评估 老年学 人口 环境卫生 星团(航天器) 危险分层 内科学 计算机安全 计算机科学 程序设计语言
作者
Norbert Stefan,Matthias B. Schulze
出处
期刊:The Lancet Diabetes & Endocrinology [Elsevier BV]
卷期号:11 (6): 426-440 被引量:166
标识
DOI:10.1016/s2213-8587(23)00086-4
摘要

Among 20 leading global risk factors for years of life lost in 2040, reference forecasts point to three metabolic risks—high blood pressure, high BMI, and high fasting plasma glucose—as being the top risk variables. Building upon these and other risk factors, the concept of metabolic health is attracting much attention in the scientific community. It focuses on the aggregation of important risk factors, which allows the identification of subphenotypes, such as people with metabolically unhealthy normal weight or metabolically healthy obesity, who strongly differ in their risk of cardiometabolic diseases. Since 2018, studies that used anthropometrics, metabolic characteristics, and genetics in the setting of cluster analyses proposed novel metabolic subphenotypes among patients at high risk (eg, those with diabetes). The crucial point now is whether these subphenotyping strategies are superior to established cardiometabolic risk stratification methods regarding the prediction, prevention, and treatment of cardiometabolic diseases. In this Review, we carefully address this point and conclude, firstly, regarding cardiometabolic risk stratification, in the general population both the concept of metabolic health and the cluster approaches are not superior to established risk prediction models. However, both subphenotyping approaches might be informative to improve the prediction of cardiometabolic risk in subgroups of individuals, such as those in different BMI categories or people with diabetes. Secondly, the applicability of the concepts by treating physicians and communication of the cardiometabolic risk with patients is easiest using the concept of metabolic health. Finally, the approaches to identify cardiometabolic risk clusters in particular have provided some evidence that they could be used to allocate individuals to specific pathophysiological risk groups, but whether this allocation is helpful for prevention and treatment still needs to be determined.
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
我是老大应助吱吱吱吱采纳,获得10
1秒前
Ccccn完成签到,获得积分10
11秒前
20秒前
TAOS发布了新的文献求助10
24秒前
26秒前
Gouki完成签到 ,获得积分10
29秒前
俊逸吐司完成签到 ,获得积分10
33秒前
ding应助TAOS采纳,获得10
34秒前
lyh完成签到,获得积分10
36秒前
香蕉觅云应助谦让鹏涛采纳,获得10
38秒前
852应助谦让鹏涛采纳,获得10
38秒前
histamin完成签到,获得积分10
38秒前
46秒前
stuhwt发布了新的文献求助10
53秒前
59秒前
小蘑菇应助科研通管家采纳,获得10
59秒前
1分钟前
1分钟前
zz发布了新的文献求助10
1分钟前
Cdragon完成签到,获得积分10
1分钟前
LRRRrRT发布了新的文献求助10
1分钟前
choo完成签到,获得积分10
1分钟前
Chouvikin完成签到,获得积分10
1分钟前
位青完成签到,获得积分10
1分钟前
1分钟前
bbihk完成签到,获得积分10
1分钟前
犹豫惜萱完成签到,获得积分10
1分钟前
Eric完成签到,获得积分10
1分钟前
ding应助wanfei采纳,获得10
1分钟前
张欢馨应助hujushan采纳,获得10
1分钟前
SciGPT应助纪年采纳,获得20
1分钟前
打打应助芊芊墨采纳,获得10
1分钟前
电量过低完成签到 ,获得积分10
1分钟前
木十四完成签到 ,获得积分10
1分钟前
Jayzie完成签到 ,获得积分10
1分钟前
1分钟前
思源应助第五彧轩采纳,获得10
2分钟前
Angora完成签到,获得积分10
2分钟前
2分钟前
wanfei发布了新的文献求助10
2分钟前
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
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Picture this! Including first nations fiction picture books in school library collections 1500
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
CLSI M100 Performance Standards for Antimicrobial Susceptibility Testing 36th edition 400
Cancer Targets: Novel Therapies and Emerging Research Directions (Part 1) 400
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 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6362003
求助须知:如何正确求助?哪些是违规求助? 8175696
关于积分的说明 17223950
捐赠科研通 5416765
什么是DOI,文献DOI怎么找? 2866548
邀请新用户注册赠送积分活动 1843754
关于科研通互助平台的介绍 1691516