Association of baseline remnant cholesterol independent of LDL-cholesterol with newly diagnosed diabetes in the Chinese population

糖尿病 内科学 胆固醇 基线(sea) 低密度脂蛋白胆固醇 医学 总胆固醇 人口 中国人口 联想(心理学) 内分泌学 生物 基因型 环境卫生 遗传学 心理学 基因 渔业 心理治疗师
作者
Yulu Yang,Xuehan Li,Jianwu Huang,Jiacheng Wu,Yalei Wang,Hao Chen,Zhihua Qiu,Zihua Zhou
标识
DOI:10.17305/bb.2024.11167
摘要

Remnant cholesterol (RC) is highly regarded in the cardiovascular field; however, its relationship with new-onset diabetes remains unclear. This study aimed to investigate the relationship between RC and the risk of developing diabetes, as well as its interaction with low-density lipoprotein cholesterol (LDL-c). This was a secondary analysis of a retrospective cohort study based on a Chinese population. A multivariate Cox proportional hazards regression was initially employed to assess the relationship between RC and newly diagnosed diabetes. This was followed by a subgroup analysis to explore intergroup heterogeneity. A clinical prediction model was then developed. Finally, the study further analyzed the interactions between LDL-c and RC. After adjusting for confounding factors, RC was significantly associated with an increased risk of diabetes (HR = 1.46, 95% confidence interval [CI] 1.36–1.57). Furthermore, this relationship was nonlinear, with an inflection point of 0.48 identified through the piecewise model. Subgroup analysis indicated that the association was more pronounced in individuals under 60 years and those with a body mass index < 24 kg/m2 (P for interaction = 0.0004, <0.0001, respectively). RC proved to be a more effective predictor of diabetes compared to other lipid profiles, and the clinical prediction model was successfully constructed. Notably, individuals in the low LDL-c/high RC group were found to have a 1.41-fold (95% CI 1.281.55) greater risk compared to those in the low LDL-c/low RC group. Significant correlations were observed between baseline RC levels and the risk of new-onset diabetes. Elevated RC was a strong predictor of diabetes risk, irrespective of LDL-c levels.

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

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
1秒前
shlw发布了新的文献求助10
5秒前
奥里给完成签到 ,获得积分10
13秒前
活ni的pig完成签到 ,获得积分10
15秒前
科研打工人完成签到,获得积分10
22秒前
细心的向日葵完成签到,获得积分10
24秒前
细雨听风完成签到,获得积分10
25秒前
卓诗云发布了新的文献求助10
25秒前
熊如懿小主完成签到 ,获得积分10
27秒前
anna521212完成签到 ,获得积分10
29秒前
yangy115完成签到,获得积分10
30秒前
卓诗云完成签到,获得积分10
37秒前
乐乐应助shlw采纳,获得10
39秒前
40秒前
ZHX完成签到 ,获得积分10
40秒前
山雀完成签到,获得积分10
40秒前
吉以寒发布了新的文献求助10
44秒前
黑粉头头完成签到,获得积分10
49秒前
xcwy完成签到,获得积分10
50秒前
zcbb完成签到,获得积分10
50秒前
bgt完成签到 ,获得积分10
50秒前
林夕完成签到 ,获得积分10
50秒前
vv完成签到 ,获得积分10
50秒前
Wang完成签到,获得积分10
52秒前
jhcraul完成签到,获得积分10
55秒前
TTDY完成签到 ,获得积分10
1分钟前
孙尧芳完成签到 ,获得积分10
1分钟前
不安士晋完成签到,获得积分10
1分钟前
萨格完成签到 ,获得积分10
1分钟前
凉面完成签到 ,获得积分10
1分钟前
鞘皮完成签到,获得积分10
1分钟前
文与武完成签到 ,获得积分10
1分钟前
你在教我做事啊完成签到 ,获得积分10
1分钟前
jiaozitop完成签到,获得积分10
1分钟前
小呆瓜与鱼完成签到 ,获得积分10
1分钟前
醒醒完成签到 ,获得积分10
1分钟前
缘分完成签到,获得积分10
1分钟前
夏之完成签到,获得积分10
1分钟前
Ruuo616完成签到 ,获得积分10
1分钟前
大饼子圆完成签到 ,获得积分10
1分钟前
高分求助中
歯科矯正学 第7版(或第5版) 1004
The late Devonian Standard Conodont Zonation 1000
Nickel superalloy market size, share, growth, trends, and forecast 2023-2030 1000
Smart but Scattered: The Revolutionary Executive Skills Approach to Helping Kids Reach Their Potential (第二版) 1000
PraxisRatgeber: Mantiden: Faszinierende Lauerjäger 700
A new species of Coccus (Homoptera: Coccoidea) from Malawi 500
Zeitschrift für Orient-Archäologie 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3239043
求助须知:如何正确求助?哪些是违规求助? 2884330
关于积分的说明 8232969
捐赠科研通 2552367
什么是DOI,文献DOI怎么找? 1380706
科研通“疑难数据库(出版商)”最低求助积分说明 649071
邀请新用户注册赠送积分活动 624787