已入深夜,您辛苦了!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!祝你早点完成任务,早点休息,好梦!

Prediction of 10-Year Cardiovascular Disease Risk, by Diabetes status and Lipoprotein-a levels; the HellenicSCORE II+

医学 置信区间 内科学 糖尿病 逻辑回归 人口 血压 优势比 体质指数 人口学 内分泌学 环境卫生 社会学
作者
Demosthenes B. Panagiotakos,Christina Chrysohoou,Christos Pitsavos,Konstantinos Tsioufis
出处
期刊:Hellenic Journal of Cardiology [Elsevier BV]
卷期号:79: 3-14 被引量:4
标识
DOI:10.1016/j.hjc.2023.10.001
摘要

The aim of this study was to develop an updated model to predict10-year cardiovascular disease (CVD) risk for Greek adults, i.e., the HellenicSCORE II+, based on smoking, systolic blood pressure (SBP), total and High-Density-Lipoprotein-(HDL) cholesterol levels, and stratified by age group, sex, history of diabetes, and Lipoprotein (Lp)-a levels. Individual CVD risk scores were calculated through logit-function models, using the beta-coefficients derived from SCORE2. The Attica Study data were used for the calibration (3,042 participants, aged 45(14) years; 49.1% men). Discrimination ability of the HellenicSCORE II+ was assessed using C-index (range 0-1), adjusted for competing risks. The mean HellenicSCORE II+ score was 6.3% (95% Confidence Interval (CI) 5.9% to 6.6%) for men and 3.7% (95% CI 3.5% to 4.0%) for women (p<0.001), and were higher compared to the relevant SCORE2; 23.5% of men were classified as low risk, 40.2% as moderate and 36.3% as high risk, whereas the corresponding percentages for women were 56.2%, 18.6% and 25.2%. C-statistic index was 0.88 for women and 0.79 for men, when the HellenicSCORE II+ was applied to the ATTICA Study data, suggesting very good accuracy. Stratified analysis by Lp(a) levels led to a 4% improvement in correct classification among participants with high Lp(a). HellenicSCORE II+ values were higher than SCORE2, confirming that the Greek population is at moderate-to-high CVD risk. Stratification by Lp(a) levels may assist to better identify individuals at high CVD risk.

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
呀呀呀发布了新的文献求助10
刚刚
L1nyun发布了新的文献求助10
1秒前
有病早治完成签到 ,获得积分10
1秒前
土豆兵完成签到,获得积分10
3秒前
4秒前
Qu完成签到 ,获得积分10
4秒前
Evan发布了新的文献求助30
5秒前
boogiepop发布了新的文献求助10
5秒前
zsj发布了新的文献求助10
5秒前
辛酸有很多种完成签到,获得积分20
8秒前
8秒前
所所的应助被让地球种满香菜采纳,获得10
8秒前
拾光完成签到,获得积分10
10秒前
清河发布了新的文献求助10
11秒前
FashionBoy的应助被pipihere采纳,获得10
11秒前
CipherSage的应助被文静碧琴采纳,获得10
12秒前
12秒前
拾光发布了新的文献求助10
14秒前
CipherSage的应助被双儿采纳,获得10
15秒前
15秒前
大个的应助被哔哩卟噜采纳,获得10
16秒前
汉堡包的应助被xsx采纳,获得10
18秒前
寒冷紫槐发布了新的文献求助10
18秒前
20秒前
23秒前
23秒前
zsj发布了新的文献求助10
24秒前
25秒前
极限001的应助被云晓采纳,获得30
27秒前
27秒前
WYP完成签到,获得积分10
28秒前
JIW发布了新的文献求助10
28秒前
zhu发布了新的文献求助30
28秒前
29秒前
dasfsdf完成签到,获得积分10
29秒前
kk关闭了kk的文献求助
32秒前
32秒前
34秒前
清爽老九的应助被温暖砖头采纳,获得10
37秒前
黄凯发布了新的文献求助10
37秒前
高分求助中
(应助此贴封号)通过应助OA文献获取积分 10000
Rosenblum, Global Change Biology 800
Computational Chemical Reaction Engineering: Modeling, Simulation, and Design with MATLAB 600
Organizational Behavior 510
Management and the Arts 510
A Will for the Machine: Computerization, Automation, and the Arts in South Africa 400
Decentring Leadership 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 计算机科学 工程类 纳米技术 内科学 物理 有机化学 化学工程 生物化学 复合材料 光电子学 细胞生物学 心理学 量子力学 催化作用 物理化学 电极
热门帖子
关注 科研通微信公众号,转发送积分 7809285
求助须知:如何正确求助?哪些是违规求助? 9341536
关于积分的说明 20507353
捐赠科研通 7401778
什么是DOI,文献DOI怎么找? 3329061
关于科研通互助平台的介绍 2475843
邀请新用户注册赠送积分活动 2347610