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
淡淡的大树完成签到,获得积分10
刚刚
阿巴阿巴发布了新的文献求助10
1秒前
11发布了新的文献求助10
1秒前
1秒前
刘畅发布了新的文献求助10
1秒前
桐桐应助momo6采纳,获得10
2秒前
布同完成签到,获得积分0
3秒前
科研通AI6.3应助香香采纳,获得10
3秒前
简单人杰发布了新的文献求助10
3秒前
超帅的哒发布了新的文献求助10
4秒前
LiLi完成签到,获得积分10
6秒前
南乔星发布了新的文献求助10
6秒前
MikyY完成签到,获得积分10
7秒前
7秒前
刘畅完成签到,获得积分10
8秒前
8秒前
爆米花应助Sophie_W采纳,获得10
9秒前
9秒前
汉堡包应助11采纳,获得10
9秒前
哭泣的芷容完成签到,获得积分10
10秒前
10秒前
超帅的哒完成签到,获得积分10
10秒前
过山车应助科研狗采纳,获得52
11秒前
小二郎应助哈哈哈采纳,获得10
11秒前
小小发布了新的文献求助30
11秒前
贪婪卡比兽完成签到,获得积分10
12秒前
13秒前
君君应助眯眯眼的山柳采纳,获得10
13秒前
哆啦A梦发布了新的文献求助10
13秒前
阮柒发布了新的文献求助30
13秒前
13秒前
cjcbb发布了新的文献求助10
14秒前
14秒前
Jason完成签到 ,获得积分10
14秒前
ZhenyuShang发布了新的文献求助10
14秒前
15秒前
科研通AI6.2应助清秀烤鸡采纳,获得10
15秒前
15秒前
段汶发布了新的文献求助10
16秒前
wonder123完成签到,获得积分10
16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
日本現代怪異事典 副読本 700
Concise Introduction to Heritage Studies 650
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 650
Machine Learning for Asset Management and Pricing 600
Numerical analysis of the coupled atmosphere-ocean models (CAO II). II 600
Models for the coupled atmosphere and ocean 600
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 7382344
求助须知:如何正确求助?哪些是违规求助? 8989571
关于积分的说明 19122338
捐赠科研通 7021195
什么是DOI,文献DOI怎么找? 3227172
关于科研通互助平台的介绍 2390203
邀请新用户注册赠送积分活动 2208038