The predict value of serum/urocystatin C on acute kidney injury in elderly patients with sepsis

医学 败血症 急性肾损伤 内科学 胃肠病学 价值(数学) 重症监护医学 计算机科学 机器学习
作者
Zhixiang Bian,Rui Zhu,Shunjie Chen
出处
期刊:Experimental Gerontology [Elsevier BV]
卷期号:155: 111576-111576 被引量:10
标识
DOI:10.1016/j.exger.2021.111576
摘要

To evaluate the predict value of serum/urocystatin C in acute kidney injury (AKI) in elderly patients with sepsis. A retrospective study was performed and 80 senile patients with sepsis in ** hospital of China was included. According to the diagnosis of AKI, all patients were divided into non-AKI group and AKI group. The clinical characteristics, laboratory and physiological indicators of the two groups were compared. The receiver operating characteristic curve (ROC) was used to analyze the accuracy of the variables, including serum cystatin C, urocystatin C, and serum creatinine, to predict the occurrence of AKI in patients with sepsis. Of the 80 elderly patients with sepsis in China, 29 patients had AKI. Compared with the non-AKI group, patients in the AKI group had higher APACHE II scores, higher SOFA scores, higher procalcitonin, and lower mean arterial pressure (P < 0.05). The levels of serum cystatin C, urocystatin C, and serum creatinine in the AKI group were significantly higher than those in the non-AKI group (P < 0.05), while the difference in intensive care unit (ICU) mortality rate between the two groups was not significantly different (P > 0.05). The ROC curve showed that the area under the curve of serum cystatin C was 0.893, the area under the curve of urocystatin C was 0.898, and the area under the curve of serum creatinine was 0.652. Serum cystatin and urocystatin could be used to predict the occurrence of AKI in elderly patients with sepsis.
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
平贝花完成签到,获得积分10
5秒前
8秒前
8秒前
yu完成签到,获得积分10
12秒前
13秒前
冰雪物语发布了新的文献求助10
13秒前
15秒前
蓝天发布了新的文献求助30
15秒前
收皮皮完成签到 ,获得积分10
15秒前
16秒前
干净的冰旋完成签到,获得积分10
16秒前
英俊的小懒虫完成签到 ,获得积分10
18秒前
Gabriel发布了新的文献求助10
18秒前
多情嫣然完成签到,获得积分10
19秒前
蜻蜓完成签到 ,获得积分10
20秒前
21秒前
yongtao发布了新的文献求助10
21秒前
老艺人完成签到,获得积分10
23秒前
Riverchase应助Gabriel采纳,获得10
27秒前
Riverchase应助Gabriel采纳,获得10
27秒前
酷炫的世立应助Gabriel采纳,获得10
27秒前
28秒前
泪是雨的旋律完成签到 ,获得积分10
29秒前
随风完成签到,获得积分10
35秒前
Ferdinand_Foch完成签到,获得积分10
36秒前
Alex完成签到,获得积分0
36秒前
Zwj完成签到 ,获得积分10
36秒前
想发JHM完成签到,获得积分10
36秒前
37秒前
KEKE完成签到 ,获得积分10
40秒前
小yang完成签到 ,获得积分10
41秒前
42秒前
xxxgoldxsx发布了新的文献求助10
42秒前
43秒前
Accpted河豚完成签到,获得积分10
44秒前
45秒前
乃春完成签到 ,获得积分10
45秒前
传奇3应助YYY采纳,获得10
46秒前
zzt33完成签到,获得积分10
48秒前
zhengzhao完成签到,获得积分10
48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
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Various Faces of Animal Metaphor in English and Polish 800
Signals, Systems, and Signal Processing 610
Superabsorbent Polymers: Synthesis, Properties and Applications 500
Photodetectors: From Ultraviolet to Infrared 500
On the Dragon Seas, a sailor's adventures in the far east 500
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 6351150
求助须知:如何正确求助?哪些是违规求助? 8165811
关于积分的说明 17184435
捐赠科研通 5407334
什么是DOI,文献DOI怎么找? 2862894
邀请新用户注册赠送积分活动 1840426
关于科研通互助平台的介绍 1689539