The aggregate index of systemic inflammation (AISI): a novel predictor for hypertension

医学 四分位数 混淆 内科学 全身炎症 全国健康与营养检查调查 比例危险模型 体质指数 全国死亡指数 肥胖 炎症 心脏病学 置信区间 人口 危险系数 环境卫生
作者
Jiaming Xiu,Xiaoxi Lin,Q Chen,Ping Yu,Jin Song Lu,Yingchi Yang,Weihua Chen,Kunming Bao,Junjie Wang,Jing Zhu,Xiaoying Zhang,Yuxiong Pan,Jiabin Tu,Kaihong Chen,Liling Chen
出处
期刊:Frontiers in Cardiovascular Medicine [Frontiers Media SA]
卷期号:10 被引量:1
标识
DOI:10.3389/fcvm.2023.1163900
摘要

Inflammation plays an important role in the pathophysiology of hypertension (HTN). Aggregate index of systemic inflammation (AISI), as a new inflammatory and prognostic marker has emerged recently. Our goal was to determine whether there was a relationship between HTN and AISI.We analyzed patients with HTN from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018. The primary end point was cardiovascular mortality. A total of 23,765 participants were divided into four groups according to the AISI quartile level. The association between AISI and cardiovascular mortality in patients with HTN was assessed by survival curves and Cox regression analyses based on NHANES recommended weights.High levels of AISI were significantly associated with cardiovascular mortality in patients with HTN. After full adjustment for confounders, there was no significant difference in the risk of cardiovascular mortality in Q2 and Q3 compared to Q1, while Q4 (HR: 1.91, 95% CI: 1.42-2.58; P < 0.001) had a higher risk of cardiovascular mortality compared to Q1. Results remained similar in subgroup analyses stratified by age (P for interaction = 0.568), gender (P for interaction = 0.059), and obesity (P for interaction = 0.289).In adults with HTN, elevated AISI levels are significantly associated with an increased risk of cardiovascular mortality and may serve as an early warning parameter for poor prognosis.

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
星辰坠于海应助LLY采纳,获得10
1秒前
weixin112233完成签到,获得积分10
2秒前
1526完成签到,获得积分10
2秒前
土豆丝炒姜丝完成签到,获得积分10
2秒前
2秒前
酷波er应助xiaomuaixuexi采纳,获得10
2秒前
humanmad发布了新的文献求助30
3秒前
3秒前
搜集达人应助郝宇采纳,获得10
3秒前
潘潘发布了新的文献求助10
3秒前
3秒前
圣甲虫完成签到 ,获得积分10
4秒前
无线电报发布了新的文献求助10
4秒前
jinxixi完成签到,获得积分10
5秒前
5秒前
111111完成签到 ,获得积分10
5秒前
Emma施施完成签到,获得积分10
5秒前
温柔的语柔完成签到,获得积分10
6秒前
贪吃完成签到,获得积分10
6秒前
6秒前
6秒前
Aimee完成签到 ,获得积分10
6秒前
CodeCraft应助李志采纳,获得10
7秒前
科研阳完成签到,获得积分10
7秒前
叨叨小夫夫完成签到,获得积分10
7秒前
青丝挽情丝完成签到,获得积分10
8秒前
草上飞发布了新的文献求助10
8秒前
Nariy完成签到,获得积分10
8秒前
8秒前
琯柠完成签到 ,获得积分10
8秒前
大力惜海发布了新的文献求助10
9秒前
9秒前
Poppy完成签到,获得积分10
9秒前
9秒前
陈露佳发布了新的文献求助10
9秒前
zhongying完成签到 ,获得积分10
9秒前
9秒前
淡然水蜜桃完成签到,获得积分10
10秒前
cling完成签到,获得积分20
10秒前
10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
Encyclopedia of Reproduction Third Edition 3000
Comprehensive Methanol Science Production, Applications, and Emerging Technologies 2000
From Victimization to Aggression 1000
化妆品原料学 1000
小学科学课程与教学 500
Study and Interlaboratory Validation of Simultaneous LC-MS/MS Method for Food Allergens Using Model Processed Foods 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5645458
求助须知:如何正确求助?哪些是违规求助? 4768941
关于积分的说明 15029289
捐赠科研通 4804094
什么是DOI,文献DOI怎么找? 2568703
邀请新用户注册赠送积分活动 1525977
关于科研通互助平台的介绍 1485604